Publications
Browse the latest research or search the publication library by title, author, or keyword.
Loading publications…
5285517
1
apa
50
date
desc
552
https://isvb.org/wp-content/plugins/zotpress/
%7B%22status%22%3A%22success%22%2C%22updateneeded%22%3Afalse%2C%22instance%22%3Afalse%2C%22meta%22%3A%7B%22request_last%22%3A50%2C%22request_next%22%3A50%2C%22used_cache%22%3Atrue%7D%2C%22data%22%3A%5B%7B%22key%22%3A%22EZ5Y8U9R%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A9948199%2C%22username%22%3A%22Alisakrause%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Falisakrause%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22parsedDate%22%3A%222026-08-27%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3B%26lt%3Bi%26gt%3BFrontiers%20%7C%20Bridge2AI%20Voice%3A%20Voice%20Artificial%20Intelligence%20Symposium%26lt%3B%5C%2Fi%26gt%3B.%20%282026%29.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Fbooks%5C%2FBridge2AI_Voice_Voice_Artificial_Intelligence_Symposium%5C%2F12162%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Fbooks%5C%2FBridge2AI_Voice_Voice_Artificial_Intelligence_Symposium%5C%2F12162%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22book%22%2C%22title%22%3A%22Frontiers%20%7C%20Bridge2AI%20Voice%3A%20Voice%20Artificial%20Intelligence%20Symposium%22%2C%22creators%22%3A%5B%5D%2C%22abstractNote%22%3A%22This%20book%20presents%20a%20curated%20collection%20of%20abstracts%20from%20the%202024%20Bridge2AI-Voice%20Symposium%20poster%20competition%2C%20a%20cornerstone%20event%20showcasing%20the%20latest%20research%20and%20innovations%20in%20the%20field%20of...%22%2C%22date%22%3A%222026-08-27%22%2C%22originalDate%22%3A%22%22%2C%22originalPublisher%22%3A%22%22%2C%22originalPlace%22%3A%22%22%2C%22format%22%3A%22%22%2C%22ISBN%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Fbooks%5C%2FBridge2AI_Voice_Voice_Artificial_Intelligence_Symposium%5C%2F12162%22%2C%22ISSN%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222026-09-10T18%3A24%3A36Z%22%7D%7D%2C%7B%22key%22%3A%22PFYFGM3H%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Jenkins%20et%20al.%22%2C%22parsedDate%22%3A%222026-07-01%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BJenkins%2C%20P.%20D.%2C%20Bedrick%2C%20S.%2C%20Karstens%2C%20L.%2C%20Hersh%2C%20W.%2C%20the%20Bridge2AI-Voice%20Consortium%2C%20%26amp%3B%20Dorr%2C%20D.%20A.%20%282026%29.%20From%20voice%20biomarkers%20to%20telemedicine%20screening%3A%20developing%20and%20evaluating%20a%20voice-based%20AI%20model%20for%20laryngeal%20lesion%20detection%20using%20the%20Bridge2AI-Voice%20dataset.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Digital%20Health%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B8%26lt%3B%5C%2Fi%26gt%3B.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2026.1846369%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2026.1846369%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22From%20voice%20biomarkers%20to%20telemedicine%20screening%3A%20developing%20and%20evaluating%20a%20voice-based%20AI%20model%20for%20laryngeal%20lesion%20detection%20using%20the%20Bridge2AI-Voice%20dataset%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Phillip%20D.%22%2C%22lastName%22%3A%22Jenkins%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Bedrick%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lisa%22%2C%22lastName%22%3A%22Karstens%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22William%22%2C%22lastName%22%3A%22Hersh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22the%20Bridge2AI-Voice%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%20A.%22%2C%22lastName%22%3A%22Dorr%22%7D%5D%2C%22abstractNote%22%3A%22BackgroundThe%20human%20voice%20contains%20rich%20acoustic%20information%20indicative%20of%20laryngeal%20pathology%2C%20yet%20current%20screening%20relies%20on%20resource-intensive%20in-person%20laryngoscopy.%20While%20artificial%20intelligence%20has%20shown%20promise%20for%20voice%20analysis%2C%20progress%20has%20been%20limited%20by%20small%2C%20inconsistent%20datasets%20and%20challenges%20to%20clinical%20translation.%20The%20Bridge2AI-Voice%20initiative%20addresses%20these%20barriers%20by%20providing%20a%20large-scale%2C%20ethically%20sourced%20dataset%20with%20standardized%2C%20privacy-preserving%20derived%20features.ObjectiveTo%20determine%20whether%20the%20derived-feature%20release%20of%20Bridge2AI-Voice%20v3.0.0%20can%20support%20a%20high-sensitivity%20screening%20model%20for%20laryngeal%20lesions%20and%20to%20evaluate%20its%20translational%20readiness%20using%20telemedicine%20implementation%20frameworks.MethodsWe%20analyzed%20data%20from%20205%20adult%20participants%20%28136%20controls%2C%2052%20benign%20vocal%20fold%20lesions%2C%2013%20precancerous%20lesions%2C%204%20laryngeal%20cancer%29%20drawn%20from%20the%20Bridge2AI-Voice%20v3.0.0%20derived-feature%20release.%20An%20L2-regularized%20logistic%20regression%20model%20was%20fit%20to%20131%20OpenSMILE%20static%20acoustic%20features%20with%20age%20and%20sex%20at%20birth%2C%20evaluated%20under%20participant-level%20stratified%2010-fold%20nested%20cross-validation.%20Inner-fold%20cross-validation%20was%20used%20for%20operating-point%20threshold%20selection.%20Pre-specified%20validity%20tests%20against%20age%20confounding%20included%20a%20DeLong%20comparison%20against%20an%20age-only%20baseline%20and%20an%20age-stratified%20label%20permutation%20test.%20Alternative%20feature%20modalities%20%28SPARC%20articulatory%20features%2C%20Mel%20spectrogram%20derivatives%2C%20and%20multimodal%20combinations%29%20and%20alternative%20classifier%20families%20were%20evaluated%20as%20robustness%20checks.ResultsThe%20OpenSMILE-based%20model%20achieved%20cross-validated%20AUC%200.812%20%2895%25%20CI%200.744%5Cu20130.876%29%2C%20with%20operating-point%20sensitivity%200.870%20%2895%25%20CI%200.767%5Cu20130.939%29%20and%20specificity%200.566%20%2895%25%20CI%200.479%5Cu20130.651%29.%20Model%20discrimination%20significantly%20exceeded%20an%20age-only%20baseline%20%28DeLong%20p%20%3D%200.0008%29%20and%20survived%20age-stratified%20label%20permutation%20%28observed%20AUC%200.812%20vs.%20null%20mean%200.553%2C%20p%20%3D%200.0099%29.%20Subgroup%20analysis%20showed%20approximately%20consistent%20sensitivity%20across%20benign%20%280.865%29%20and%20precancerous%20%280.846%29%20lesion%20subgroups.%20Alternative%20feature%20modalities%20did%20not%20provide%20incremental%20discriminative%20information%20beyond%20OpenSMILE%2C%20and%20alternative%20classifier%20families%20produced%20AUCs%20within%20bootstrap%20confidence%20intervals%20of%20the%20primary%20model.ConclusionsDerived%20acoustic%20features%20from%20the%20Bridge2AI-Voice%20v3.0.0%20release%20combined%20with%20basic%20demographic%20information%20support%20cross-validated%20discrimination%20of%20vocal%20fold%20lesions%20consistent%20with%20the%20upper%20range%20of%20published%20voice-based%20laryngeal%20pathology%20classifiers.%20The%20result%20is%20presented%20as%20a%20candidate%20signal%20warranting%20confirmatory%20investigation%20in%20a%20larger%2C%20prospectively%20recruited%20cohort.%22%2C%22date%22%3A%222026-07-01%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffdgth.2026.1846369%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Fjournals%5C%2Fdigital-health%5C%2Farticles%5C%2F10.3389%5C%2Ffdgth.2026.1846369%5C%2Ffull%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-253X%22%2C%22language%22%3A%22English%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-07-20T18%3A06%3A09Z%22%7D%7D%2C%7B%22key%22%3A%22N78EDDN4%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Ebraheem%20et%20al.%22%2C%22parsedDate%22%3A%222026-06-24%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BEbraheem%2C%20M.%2C%20Toghranegar%2C%20J.%2C%20Bridge2AI-Voice%20Consortium%2C%20Bensoussan%2C%20Y.%2C%20%26amp%3B%20Templeton%2C%20J.%20M.%20%282026%29.%20Explainable%20and%20Interpretable%20AI%20for%20Voice%20and%20Speech%20Analysis%20in%20Clinical%20Care%3A%20Systematic%20Review.%20%26lt%3Bi%26gt%3BJournal%20of%20Medical%20Internet%20Research%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B28%26lt%3B%5C%2Fi%26gt%3B%2C%20e83790%26%23x2013%3Be83790.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.2196%5C%2F83790%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.2196%5C%2F83790%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Explainable%20and%20Interpretable%20AI%20for%20Voice%20and%20Speech%20Analysis%20in%20Clinical%20Care%3A%20Systematic%20Review%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mohamed%22%2C%22lastName%22%3A%22Ebraheem%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jamie%22%2C%22lastName%22%3A%22Toghranegar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22Bridge2AI-Voice%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22John%20Michael%22%2C%22lastName%22%3A%22Templeton%22%7D%5D%2C%22abstractNote%22%3A%22Abstract%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Background%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Driven%20by%20recent%20advances%20in%20artificial%20intelligence%20%28AI%29%2C%20particularly%20in%20medicine%2C%20audio-based%20voice%20and%20speech%20biomarkers%20are%20increasingly%20investigated%20for%20various%20medical%20applications%20as%20a%20complementary%20or%20even%20alternative%20modality%20to%20traditional%20medical%20devices.%20The%20adoption%20of%20deep%20learning%20techniques%20in%20recent%20literature%20is%20motivated%20by%20their%20superior%20performance%20compared%20to%20classical%20machine%20learning%20methods.%20However%2C%20ethical%20and%20regulatory%20concerns%20regarding%20the%20black-box%20nature%20of%20these%20models%20have%20limited%20their%20integration%20into%20clinical%20workflows.%20Consequently%2C%20explainable%20artificial%20intelligence%20%28XAI%29%20has%20recently%20been%20used%20to%20address%20this%20issue%20by%20generating%20explanations%20for%20opaque%20model%20outputs.%20Ideally%2C%20medical%20XAI%20systems%20aim%20to%20provide%20human-understandable%2C%20clinically%20grounded%20explanations%20essential%20for%20enhanced%20AI%20trustworthiness%20and%2C%20thereby%2C%20facilitate%20adoption%20into%20real-world%20clinical%20settings.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Objective%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20We%20conduct%20a%20systematic%20literature%20review%20of%20XAI%20methods%20applied%20for%20explaining%20deep%20learning%20techniques%20in%20audio-based%20voice%20and%20speech%20clinical%20applications.%20We%20aim%20to%20identify%20what%20XAI%20methods%20have%20been%20used%20to%20explain%20the%20decisions%20of%20deep%20learning%20voice%20and%20speech%20AI%20systems%20in%20health%20care%2C%20as%20well%20as%20XAI-informed%20insights.%20Additionally%2C%20we%20aim%20to%20contextualize%20these%20findings%20with%20respect%20to%20clinical%20applicability%20and%20stakeholder%20relevance.%20Lastly%2C%20we%20identify%20opportunities%20and%20recommendations%20for%20future%20clinical%20audio%20XAI%20design.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Methods%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20We%20used%20PRISMA%20%28Preferred%20Reporting%20Items%20for%20Systematic%20Reviews%20and%20Meta-Analyses%29.%20Six%20electronic%20databases%20%28IEEE%20Xplore%2C%20ACM%20Digital%20Library%2C%20Scopus%2C%20PubMed%2C%20Web%20of%20Science%2C%20and%20Nature%29%20were%20searched%20for%20papers%20published%20between%20January%202015%20and%20February%202025.%20Eligible%20studies%20applied%20explainability%20or%20interpretability%20methods%20to%20deep%20learning%20models%20for%20voice%20or%20speech%20audio%20in%20health%20care%20contexts.%20Risk%20of%20bias%20was%20assessed%20using%20PROBAST%2BAI%20%28Prediction%20Model%20Risk%20of%20Bias%20Assessment%20Tool%29.%20The%20results%20were%20thematically%20synthesized%20across%20explainability%20categories%2C%20input%20representations%2C%20clinical%20domains%2C%20validation%20strategies%2C%20and%20stakeholder%20considerations.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Results%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20A%20total%20of%2030%20studies%20met%20the%20inclusion%20criteria.%20These%20studies%20used%20a%20range%20of%20explainability%20approaches%2C%20including%20gradient-based%20methods%2C%20perturbation-based%20techniques%2C%20surrogate%20model%5Cu2013based%20methods%2C%20model-internal%20representation%20analyses%2C%20concept-based%20detectors%2C%20and%20attention-based%20explanations.%20Applications%20spanned%20diverse%20clinical%20domains%2C%20including%20voice%20disorders%2C%20neurodegenerative%20diseases%2C%20psychiatric%20conditions%2C%20and%20traumatic%20brain%20injury.%20Overall%2C%20results%20indicate%20that%20most%20studies%20relied%20primarily%20on%20qualitative%20interpretation%20of%20explainability%20outputs%2C%20with%20limited%20quantitative%20validation%20of%20explanation%20consistency%20across%20external%20datasets.%20Furthermore%2C%20none%20of%20the%20included%20studies%20explicitly%20conducted%20human-in-the-loop%20evaluations%20with%20relevant%20stakeholders%2C%20highlighting%20a%20substantial%20gap%20in%20stakeholder%20alignment.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Conclusions%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Current%20XAI%20practices%20in%20clinical%20voice%20and%20speech%20analysis%20are%20limited%20by%20insufficient%20validation%2C%20lack%20of%20domain-specific%20design%2C%20and%20misalignment%20with%20clinical%20stakeholder%20needs.%20This%20review%20highlights%20opportunities%20for%20developing%20validated%2C%20audio-aware%2C%20and%20stakeholder-centered%20XAI%20approaches%20to%20support%20trustworthy%20clinical%20deployment.%20Interpretation%20of%20these%20findings%20should%20consider%20limitations%20related%20to%20single-reviewer%20study%20selection%2C%20potential%20high-risk%20of%20bias%2C%20and%20the%20repeated%20use%20of%20benchmark%20datasets.%22%2C%22date%22%3A%222026-6-24%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.2196%5C%2F83790%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.jmir.org%5C%2F2026%5C%2F1%5C%2Fe83790%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%221438-8871%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222026-07-16T21%3A10%3A08Z%22%7D%7D%2C%7B%22key%22%3A%22QXMMBVTD%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Elemento%20et%20al.%22%2C%22parsedDate%22%3A%222026-05-30%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BElemento%2C%20O.%2C%20Sigaras%2C%20A.%2C%20Colonel%2C%20J.%20T.%2C%20Hajirasouliha%2C%20I.%2C%20Ghosh%2C%20S.%20S.%2C%20Bensoussan%2C%20Y.%2C%20Bridge2AI-Voice%20Consortium%2C%20%26amp%3B%20Rameau%2C%20A.%20%282026%29.%20%26lt%3Bi%26gt%3BTowards%20A%20Foundation%20Model%20for%20Clinical%20Voice%20Biomarkers%26lt%3B%5C%2Fi%26gt%3B.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.64898%5C%2F2026.05.28.26354346%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.64898%5C%2F2026.05.28.26354346%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22preprint%22%2C%22title%22%3A%22Towards%20A%20Foundation%20Model%20for%20Clinical%20Voice%20Biomarkers%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Olivier%22%2C%22lastName%22%3A%22Elemento%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexandros%22%2C%22lastName%22%3A%22Sigaras%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Joseph%20T.%22%2C%22lastName%22%3A%22Colonel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Iman%22%2C%22lastName%22%3A%22Hajirasouliha%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Satrajit%20S.%22%2C%22lastName%22%3A%22Ghosh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22Bridge2AI-Voice%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ana%5Cu00efs%22%2C%22lastName%22%3A%22Rameau%22%7D%5D%2C%22abstractNote%22%3A%22Abstract%20%5Cn%20%20%20%20%20%20%20%20%20%20Vocal%20biomarkers%2C%20encompassing%20voice%20and%20speech%20%5B1%5D%2C%20have%20largely%20been%20developed%20for%20individual%20conditions%20in%20isolation%2C%20limiting%20their%20generalizability%20across%20diseases%20and%20recording%20settings.%20To%20address%20this%2C%20we%20introduce%20VoiceFM%2C%20a%20contrastive%20model%20that%20learns%20general-purpose%20clinical%20voice%20representations%20by%20aligning%20audio%20embeddings%20with%20rich%20clinical%20metadata.%20Using%20the%20Bridge2AI-Voice%20dataset%20%28984%20primarily%20English-speaking%20adult%20participants%20%5Cu2014%20846%20used%20for%20training%20and%20138%20held%20out%20as%20a%20temporally%20separated%20validation%20cohort%20%5Cu2014%2040%2C056%20recordings%20totaling%20176%20hours%20across%205%20academic%20medical%20centers%29%2C%20VoiceFM%20pairs%20a%20fine-tuned%20Whisper%20large-v2%20encoder%20with%20a%20tabular%20transformer%20over%2044%20clinical%20features%20via%20symmetric%20InfoNCE%20loss.%20Linear%20probes%20on%20frozen%20VoiceFM%20embeddings%20achieve%20mean%20AUROC%200.952%20%5Cu00b1%200.005%20across%20five%20evaluation%20tasks%20%28control%20vs%20disease%20screening%20plus%20four%20disease%20categories%29%2C%20significantly%20outperforming%20Frozen%20Whisper%20%280.926%20%5Cu00b1%200.013%2C%20p%20%3D%200.013%29%2C%20Frozen%20HuBERT%20%280.885%20%5Cu00b1%200.017%2C%20p%20%3D%200.0009%29%2C%20and%20the%20contrastively%20trained%20VoiceFM-HuBERT%20%280.938%20%5Cu00b1%200.006%2C%20p%20%3D%200.012%29.%20On%20the%20138-participant%20held-out%20cohort%2C%20VoiceFM-Whisper%20achieves%20AUROCs%20of%200.99%20for%20Alzheimer%5Cu2019s%5C%2Fdementia%5C%2FMCI%20and%200.89%20for%20airway%20stenosis%2C%20demonstrating%20that%20the%20learned%20representations%20generalize%20to%20participants%20the%20model%20has%20never%20seen.%20VoiceFM%20representations%20transfer%20to%20three%20external%20datasets%20without%20retraining%20and%20improve%20few-shot%20classification.%20Recording%20task%20attribution%20identifies%20a%20small%20set%20of%20speech%20tasks%20that%20match%20or%20exceed%20the%20full%20battery%5Cu2019s%20performance%2C%20suggesting%20shorter%20screening%20protocols%20are%20feasible.%20Trained%20predominantly%20on%20English%20audio%2C%20VoiceFM%20transfers%20without%20fine-tuning%20to%20Spanish-language%20Parkinson%5Cu2019s%20disease%20%28PD%29%20detection%20%28NeuroVoz%2C%20107%20participants%2C%20AUROC%200.93%20%5Cu00b1%200.02%29%2C%20with%20the%20signal%20dominated%20by%20articulatory%20rather%20than%20phonatory%20features.%20A%20fine-tuned%20classifier%20achieves%20participant-level%20AUROC%200.87%20%28sustained%200.85%2C%20countdown%200.80%29%20on%20the%20mPower%20smartphone%20study%20%28585%20held-out%20participants%29.%20Together%2C%20these%20results%20show%20that%20contrastive%20alignment%20between%20voice%20and%20rich%20clinical%20metadata%20can%20serve%20as%20the%20basis%20for%20a%20clinical%20voice%20foundation%20model%2C%20producing%20a%20single%20set%20of%20transferable%20representations%20that%20generalize%20across%20diseases%2C%20languages%2C%20recording%20conditions%2C%20and%20patients%20enrolled%20after%20model%20freeze.%22%2C%22genre%22%3A%22%22%2C%22repository%22%3A%22%22%2C%22archiveID%22%3A%22%22%2C%22date%22%3A%222026-05-30%22%2C%22DOI%22%3A%2210.64898%5C%2F2026.05.28.26354346%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22http%3A%5C%2F%5C%2Fmedrxiv.org%5C%2Flookup%5C%2Fdoi%5C%2F10.64898%5C%2F2026.05.28.26354346%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222026-07-16T21%3A11%3A06Z%22%7D%7D%2C%7B%22key%22%3A%22T7CXUT4R%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22B%5Cu00e9lisle-Pipon%20et%20al.%22%2C%22parsedDate%22%3A%222026-04-10%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BB%26%23xE9%3Blisle-Pipon%2C%20J.-C.%2C%20Toghranegar%2C%20J.%2C%20%26amp%3B%20Powell%2C%20M.%20E.%20%282026%29.%20Editorial%3A%20Advancing%20vocal%20biomarkers%20and%20voice%20AI%20in%20healthcare%3A%20multidisciplinary%20focus%20on%20responsible%20and%20effective%20development%20and%20use.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Digital%20Health%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B8%26lt%3B%5C%2Fi%26gt%3B%2C%201811486.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2026.1811486%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2026.1811486%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Editorial%3A%20Advancing%20vocal%20biomarkers%20and%20voice%20AI%20in%20healthcare%3A%20multidisciplinary%20focus%20on%20responsible%20and%20effective%20development%20and%20use%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Christophe%22%2C%22lastName%22%3A%22B%5Cu00e9lisle-Pipon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jamie%22%2C%22lastName%22%3A%22Toghranegar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maria%20E.%22%2C%22lastName%22%3A%22Powell%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222026-4-10%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffdgth.2026.1811486%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Farticles%5C%2F10.3389%5C%2Ffdgth.2026.1811486%5C%2Ffull%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-253X%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-07-20T18%3A00%3A46Z%22%7D%7D%2C%7B%22key%22%3A%22PLND4248%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Kutler%20and%20Rameau%22%2C%22parsedDate%22%3A%222026-03-23%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BKutler%2C%20R.%20B.%2C%20%26amp%3B%20Rameau%2C%20A.%20%282026%29.%20Artificial%20Intelligence%20in%20Voice%20Disorders%3A%20Current%20Landscape%2C%20Emerging%20Applications%20and%20Future%20Directions.%20%26lt%3Bi%26gt%3BWorld%20Journal%20of%20Otorhinolaryngology%20-%20Head%20and%20Neck%20Surgery%26lt%3B%5C%2Fi%26gt%3B%2C%20wjo2.70103.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fwjo2.70103%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fwjo2.70103%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Artificial%20Intelligence%20in%20Voice%20Disorders%3A%20Current%20Landscape%2C%20Emerging%20Applications%20and%20Future%20Directions%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rachel%20B.%22%2C%22lastName%22%3A%22Kutler%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ana%5Cu00efs%22%2C%22lastName%22%3A%22Rameau%22%7D%5D%2C%22abstractNote%22%3A%22ABSTRACT%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Objective%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20To%20provide%20a%20comprehensive%20review%20of%20the%20current%20landscape%20of%20artificial%20intelligence%20%28AI%29%20applications%20in%20voice%20disorder%2C%20with%20emphasis%20on%20emerging%20applications%2C%20limitations%2C%20and%20future%20directions%20for%20clinical%20integration.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Methods%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Literature%20review.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Conclusion%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20AI%5Cu2010based%20voice%20analysis%20is%20a%20promising%20tool%20for%20the%20screening%20and%20monitoring%20of%20vocal%20pathology%2C%20offering%20advantages%20in%20accessibility%2C%20scalability%2C%20and%20sensitivity%20to%20subtle%20acoustic%20features.%20However%2C%20current%20models%20remain%20limited%20by%20small%20data%20sets%20and%20lack%20of%20standardization%20in%20recording%20and%20reporting%20techniques.%20To%20move%20beyond%20proof%5Cu2010of%5Cu2010concept%20studies%2C%20future%20work%20must%20focus%20on%20longitudinal%20and%20multimodal%20data%20integration%2C%20explainability%2C%20fairness%2C%20and%20validated%20frameworks%20for%20implementation.%20Emerging%20strategies%20such%20as%20edge%20computing%2C%20synthetic%20data%2C%20and%20ambient%20electronic%20health%20record%20%28EHR%29%20integration%20may%20facilitate%20scalable%2C%20privacy%5Cu2010preserving%20adoption%20in%20clinical%20settings.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%2C%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20Summary%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20Voice%20AI%2C%20also%20called%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20audiomics%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%2C%20holds%20promise%20as%20a%20non%5Cu2010invasive%2C%20accessible%20tool%20for%20screening%20and%20monitoring%20voice%20disorders%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%2C%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20but%20current%20models%20are%20limited%20by%20small%2C%20heterogeneous%20data%20sets%20and%20lack%20of%20clinical%20validation.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20Longitudinal%20monitoring%20and%20multimodal%20integration%5Cu2014combining%20voice%20with%20imaging%2C%20demographics%2C%20and%20other%20clinical%20data%5Cu2014can%20improve%20diagnostic%20accuracy%20and%20extend%20applications%20beyond%20screening%20and%20toward%20other%20applications%2C%20including%20precision%20diagnostics%20and%20therapeutics%2C%20disease%20monitoring%2C%20prognostication%2C%20and%20treatment%20outcome%20prediction%20of%20voice%20disorders.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20Scalable%20clinical%20adoption%20will%20require%20continued%20development%20of%20standards%20for%20data%20collection%20protocols%20and%20data%20format%2C%20explainable%20model%20outputs%2C%20and%20implementation%20strategies%20that%20prioritize%20privacy%2C%20equity%2C%20and%20real%5Cu2010world%20usability.%22%2C%22date%22%3A%222026-03-23%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1002%5C%2Fwjo2.70103%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fonlinelibrary.wiley.com%5C%2Fdoi%5C%2F10.1002%5C%2Fwjo2.70103%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222095-8811%2C%202589-1081%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222026-07-16T21%3A11%3A37Z%22%7D%7D%2C%7B%22key%22%3A%22XYP5UAVS%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Salvi%20Cruz%20et%20al.%22%2C%22parsedDate%22%3A%222026-03-16%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BSalvi%20Cruz%2C%20S.%2C%20Toghranegar%2C%20J.%2C%20Malin%2C%20B.%2C%20Mehra%2C%20T.%2C%20MacDonald%2C%20B.%2C%20Speights%2C%20M.%2C%20Noufi%2C%20C.%2C%20Fossat%2C%20Y.%2C%20Fagherrazi%2C%20G.%2C%20Cummins%2C%20N.%2C%20Elbeji%2C%20A.%2C%20Blatter%2C%20A.%2C%20Gelbard%2C%20A.%2C%20Arienzo%2C%20A.%2C%20Baur%2C%20S.%2C%20Wetstone%2C%20K.%2C%20Peller%2C%20J.%2C%20Au%2C%20R.%2C%20Botha%2C%20H.%2C%20%26%23x2026%3B%20Bensoussan%2C%20Y.%20%282026%29.%20Translating%20AI%20research%20into%20reality%3A%20summary%20of%20the%202025%20voice%20AI%20Symposium%20and%20Hackathon.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Digital%20Health%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B8%26lt%3B%5C%2Fi%26gt%3B%2C%201754426.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2026.1754426%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2026.1754426%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Translating%20AI%20research%20into%20reality%3A%20summary%20of%20the%202025%20voice%20AI%20Symposium%20and%20Hackathon%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Samantha%22%2C%22lastName%22%3A%22Salvi%20Cruz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jamie%22%2C%22lastName%22%3A%22Toghranegar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Bradley%22%2C%22lastName%22%3A%22Malin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tarun%22%2C%22lastName%22%3A%22Mehra%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Bob%22%2C%22lastName%22%3A%22MacDonald%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marisha%22%2C%22lastName%22%3A%22Speights%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Camille%22%2C%22lastName%22%3A%22Noufi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yan%22%2C%22lastName%22%3A%22Fossat%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Guy%22%2C%22lastName%22%3A%22Fagherrazi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nicholas%22%2C%22lastName%22%3A%22Cummins%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Abir%22%2C%22lastName%22%3A%22Elbeji%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alden%22%2C%22lastName%22%3A%22Blatter%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexander%22%2C%22lastName%22%3A%22Gelbard%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Arianna%22%2C%22lastName%22%3A%22Arienzo%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sebastien%22%2C%22lastName%22%3A%22Baur%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Katie%22%2C%22lastName%22%3A%22Wetstone%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Juli%5Cu00e1n%22%2C%22lastName%22%3A%22Peller%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rhoda%22%2C%22lastName%22%3A%22Au%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hugo%22%2C%22lastName%22%3A%22Botha%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Amir%22%2C%22lastName%22%3A%22Lahav%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Daria%22%2C%22lastName%22%3A%22Hemmerling%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Fabio%22%2C%22lastName%22%3A%22Catania%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22James%22%2C%22lastName%22%3A%22Anibal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shumit%22%2C%22lastName%22%3A%22Saha%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Oita%22%2C%22lastName%22%3A%22Coleman%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hortense%22%2C%22lastName%22%3A%22Gallois%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sophia%22%2C%22lastName%22%3A%22Avila%20Martinez%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nihar%22%2C%22lastName%22%3A%22Mahapatra%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jaskanwal%20Deep%22%2C%22lastName%22%3A%22Singh%20Sara%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Aarush%22%2C%22lastName%22%3A%22Mathur%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rupal%22%2C%22lastName%22%3A%22Patel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Konrad%22%2C%22lastName%22%3A%22Zieli%5Cu0144ski%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lampros%22%2C%22lastName%22%3A%22Kourtis%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jordan%22%2C%22lastName%22%3A%22Lerner-Ellis%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yan%22%2C%22lastName%22%3A%22Cong%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hoan%22%2C%22lastName%22%3A%22Ngo%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tanya%22%2C%22lastName%22%3A%22Talkar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Greg%22%2C%22lastName%22%3A%22Hale%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Keith%22%2C%22lastName%22%3A%22Comito%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Satrajit%22%2C%22lastName%22%3A%22Ghosh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stephanie%22%2C%22lastName%22%3A%22Watts%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Bedrick%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maria%22%2C%22lastName%22%3A%22Powell%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Christophe%22%2C%22lastName%22%3A%22B%5Cu00e9lisle-Pipon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andrea%22%2C%22lastName%22%3A%22Krussel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ishaan%22%2C%22lastName%22%3A%22Mahapatra%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ruth%22%2C%22lastName%22%3A%22Bahr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Karim%22%2C%22lastName%22%3A%22Hanna%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Cynthia%22%2C%22lastName%22%3A%22Kostelnik%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Katie%22%2C%22lastName%22%3A%22Dorsey%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22MyVan%22%2C%22lastName%22%3A%22John%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Kathleen%22%2C%22lastName%22%3A%22Curp%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ana%5Cu00efs%22%2C%22lastName%22%3A%22Rameau%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22The%20Bridge2AI-Voice%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%5D%2C%22abstractNote%22%3A%22The%202025%20Voice%20AI%20Symposium%20represented%20a%20transition%20from%20conceptual%20research%20to%20clinical%20implementation%20in%20vocal%20biomarker%20science.%20Hosted%20by%20the%20NIH-funded%20Bridge2AI-Voice%20consortium%2C%20the%20meeting%20convened%20global%20experts%20to%20address%20the%20methodological%2C%20ethical%2C%20and%20translational%20challenges%20of%20integrating%20voice-based%20artificial%20intelligence%20%28AI%29%20into%20healthcare.%20This%20mini-review%20synthesizes%20symposium%20insights%20across%20six%20domains%3A%20multimodal%20integration%2C%20FAIR%20%28Findable%2C%20Accessible%2C%20Interoperable%2C%20Reusable%29%20and%20CARE%20%28Collective%20Benefit%2C%20Authority%20to%20Control%2C%20Responsibility%2C%20Ethics%29%20data%20governance%2C%20clinical%20translation%2C%20interdisciplinary%20training%2C%20and%20cross-sector%20innovation.%20Research%20presented%20demonstrated%20voice%20as%20a%20latent%2C%20multimodal%20biomarker%20reflecting%20neurological%2C%20cardiopulmonary%2C%20and%20psychological%20states%2C%20while%20discussions%20emphasized%20ethical%20data%20practices%20and%20human-centered%20design.%20The%20implementation-focused%20panels%20underscored%20the%20importance%20of%20workflow%20alignment%20and%20usability%20for%20adoption%20in%20real-world%20care.%20Collectively%2C%20the%20symposium%20reflects%20a%20field%20advancing%20toward%20translational%20readiness%20and%20ethical%20accountability%2C%20positioning%20voice%20AI%20as%20a%20scalable%2C%20inclusive%20tool%20for%20next-generation%20healthcare.%22%2C%22date%22%3A%222026-3-16%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffdgth.2026.1754426%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Farticles%5C%2F10.3389%5C%2Ffdgth.2026.1754426%5C%2Ffull%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-253X%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-07-20T18%3A07%3A11Z%22%7D%7D%2C%7B%22key%22%3A%22V5WB72FT%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Rahman%20et%20al.%22%2C%22parsedDate%22%3A%222026-03-01%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BRahman%2C%20J.%20M.%20W.%2C%20Boyer%2C%20M.%2C%20Sanchez%2C%20V.%20A.%2C%20%26amp%3B%20Bensoussan%2C%20Y.%20%282026%29.%20Why%20Hearing%20Health%20Must%20Be%20Part%20of%20Voice%20Biomarker%20Research.%20%26lt%3Bi%26gt%3BJAMA%20Otolaryngology%26%23x2013%3BHead%20%26amp%3B%20Neck%20Surgery%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B152%26lt%3B%5C%2Fi%26gt%3B%283%29%2C%20225.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1001%5C%2Fjamaoto.2025.4836%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1001%5C%2Fjamaoto.2025.4836%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Why%20Hearing%20Health%20Must%20Be%20Part%20of%20Voice%20Biomarker%20Research%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22J.%20M.%20Warith%22%2C%22lastName%22%3A%22Rahman%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Micah%22%2C%22lastName%22%3A%22Boyer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Victoria%20A.%22%2C%22lastName%22%3A%22Sanchez%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ya%5Cu00ebl%22%2C%22lastName%22%3A%22Bensoussan%22%7D%5D%2C%22abstractNote%22%3A%22This%20Viewpoint%20explores%20the%20use%20of%20digital%20screening%20tools%20to%20identify%20voice%20biomarkers%20and%20discusses%20the%20importance%20of%20including%20hearing%20health%20as%20a%20component%20of%20voice%20biomarker%20research.%22%2C%22date%22%3A%222026-03-01%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1001%5C%2Fjamaoto.2025.4836%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fjamanetwork.com%5C%2Fjournals%5C%2Fjamaotolaryngology%5C%2Ffullarticle%5C%2F2843109%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222168-6181%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222026-07-16T21%3A14%3A08Z%22%7D%7D%2C%7B%22key%22%3A%22TLCXETAJ%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Malo%20et%20al.%22%2C%22parsedDate%22%3A%222026-02-10%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BMalo%2C%20M.-F.%2C%20Bouhouita-Guermech%2C%20S.%2C%20Gallois%2C%20H.%2C%20Ravitsky%2C%20V.%2C%20Bridge2AI%20Voice%20Consortium%2C%20%26amp%3B%20B%26%23xE9%3Blisle-Pipon%2C%20J.-C.%20%282026%29.%20Using%20voice%20and%20speech%20data%20in%20healthcare%3A%20a%20scoping%20review%20of%20the%20ethical%2C%20legal%20and%20social%20implications.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Digital%20Health%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B8%26lt%3B%5C%2Fi%26gt%3B%2C%201750111.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2026.1750111%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2026.1750111%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Using%20voice%20and%20speech%20data%20in%20healthcare%3A%20a%20scoping%20review%20of%20the%20ethical%2C%20legal%20and%20social%20implications%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marie-Fran%5Cu00e7oise%22%2C%22lastName%22%3A%22Malo%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sarah%22%2C%22lastName%22%3A%22Bouhouita-Guermech%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hortense%22%2C%22lastName%22%3A%22Gallois%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Vardit%22%2C%22lastName%22%3A%22Ravitsky%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22Bridge2AI%20Voice%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Christophe%22%2C%22lastName%22%3A%22B%5Cu00e9lisle-Pipon%22%7D%5D%2C%22abstractNote%22%3A%22Human%20voice%20and%20speech%2C%20integral%20to%20personal%20identity%20and%20social%20communication%2C%20are%20increasingly%20used%20as%20biometric%20and%20digital%20biomarkers%20in%20healthcare.%20Their%20collection%20and%20analysis%2C%20enabled%20by%20artificial%20intelligence%2C%20machine%20learning%2C%20and%20natural%20language%20processing%2C%20offer%20promising%20applications%20in%20disease%20detection%20and%20health%20monitoring.%20This%20scoping%20review%20examines%20the%20ethical%2C%20legal%2C%20and%20social%20implications%20%28ELSIs%29%20associated%20with%20using%20voice%20and%20speech%20data%20in%20healthcare.%20Following%20a%20structured%20search%20of%20four%20databases%20and%20a%20snowball%20method%2C%2065%20articles%20published%20between%202009%20and%202024%20were%20analyzed.%20The%20findings%20are%20organized%20into%20three%20main%20ELSI%20categories%3A%20ethical%20concerns%20include%20privacy%20breaches%2C%20challenges%20of%20informed%20consent%2C%20and%20the%20need%20for%20data%20validation%20and%20respect%20for%20vulnerable%20populations%3B%20social%20issues%20highlight%20biases%2C%20representational%20disparities%2C%20and%20risks%20of%20discrimination%20and%20data%20misuse%3B%20legal%20issues%20include%20unclear%20regulatory%20frameworks%2C%20conflicting%20jurisdictional%20mandates%2C%20and%20challenges%20in%20defining%20data%20ownership.%20The%20review%20reveals%20that%20while%20many%20ELSIs%20mirror%20those%20of%20other%20biomarker%20data%2C%20the%20unique%20properties%20of%20voice%20and%20speech%20require%20adapted%20frameworks%20for%20consent%2C%20data%20governance%2C%20and%20privacy%20protection.%20Technological%20limitations%2C%20dataset%20scarcity%2C%20and%20industry-academic%20divides%20exacerbate%20risks%20and%20hinder%20equitable%20development.%20Few%20studies%20deeply%20explore%20ELSIs%20in%20underrepresented%20populations%2C%20and%20there%20is%20a%20lack%20of%20robust%20empirical%20research.%20The%20review%20argues%20for%20a%20contextualist%2C%20not%20exceptionalist%2C%20approach%20to%20voice%20biomarkers%2C%20acknowledging%20both%20overlapping%20and%20unique%20challenges.%20It%20concludes%20by%20stressing%20the%20need%20for%20harmonized%20regulations%2C%20inclusive%20datasets%2C%20and%20interdisciplinary%20collaboration%20to%20ensure%20responsible%2C%20equitable%20integration%20of%20voice%20and%20speech%20technologies%20in%20healthcare.%22%2C%22date%22%3A%222026-2-10%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffdgth.2026.1750111%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Farticles%5C%2F10.3389%5C%2Ffdgth.2026.1750111%5C%2Ffull%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-253X%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-07-20T18%3A01%3A19Z%22%7D%7D%2C%7B%22key%22%3A%2236QQTAXF%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Lee%20et%20al.%22%2C%22parsedDate%22%3A%222026%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BLee%2C%20M.%2C%20Meylan%2C%20S.%2C%20Shobin%2C%20E.%2C%20the%20SpeechDx%20Consortium%2C%20Nisenbaum%2C%20L.%2C%20Sukumar%2C%20A.%2C%20%26amp%3B%20Kourtis%2C%20L.%20%282026%29.%20Digital%20speech%26%23x2010%3Bbased%20markers%20to%20advance%20prognosis%20in%20Alzheimer%26%23x2019%3Bs%20disease.%20%26lt%3Bi%26gt%3BAlzheimer%26%23x2019%3Bs%20%26amp%3B%20Dementia%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B22%26lt%3B%5C%2Fi%26gt%3B%286%29%2C%20e71489.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Falz.71489%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Falz.71489%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Digital%20speech%5Cu2010based%20markers%20to%20advance%20prognosis%20in%20Alzheimer%27s%20disease%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Melissa%22%2C%22lastName%22%3A%22Lee%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stephan%22%2C%22lastName%22%3A%22Meylan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Eli%22%2C%22lastName%22%3A%22Shobin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22the%20SpeechDx%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Laura%22%2C%22lastName%22%3A%22Nisenbaum%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Aishwarya%22%2C%22lastName%22%3A%22Sukumar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lampros%22%2C%22lastName%22%3A%22Kourtis%22%7D%5D%2C%22abstractNote%22%3A%22Abstract%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Validated%20prognostic%20tools%20are%20essential%20to%20advance%20drug%20development%20and%20clinical%20care%20in%20Alzheimer%26%23039%3Bs%20disease%2C%20particularly%20as%20the%20field%20shifts%20toward%20the%20prevention%20of%20cognitive%20decline.%20While%20progress%20has%20been%20made%20in%20developing%20blood%5Cu2010based%20biomarkers%20for%20the%20early%20detection%20of%20amyloid%20pathology%2C%20amyloid%20positivity%20alone%20does%20not%20reliably%20predict%20progression%20to%20symptomatic%20disease.%20Digital%20markers%20can%20serve%20as%20complementary%20prognostic%20tools%20to%20inform%20early%20intervention%20strategies.%20Among%20digital%20markers%2C%20speech%5Cu2010based%20markers%20offer%20a%20scalable%2C%20non%5Cu2010invasive%2C%20and%20cost%5Cu2010effective%20approach%20to%20predicting%20and%20monitoring%20cognitive%20decline.%20However%2C%20the%20development%20of%20validated%20speech%5Cu2010based%20tools%20has%20been%20constrained%20by%20the%20lack%20of%20large%2C%20multilingual%20datasets%20with%20longitudinal%20sampling%2C%20deep%20phenotyping%2C%20harmonized%20clinical%20and%20biomarker%20data%2C%20and%20adequate%20representation%20of%20preclinical%20populations.%20SpeechDx%20is%20a%203%5Cu2010year%2C%20multinational%2C%20multilingual%20observational%20study%20%28%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20n%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cu00a0%3D%5Cu00a02006%29%20designed%20to%20address%20these%20gaps%20and%20accelerate%20the%20development%20of%20speech%5Cu2010based%20tools%20to%20inform%20early%20risk%20assessment%2C%20enable%20timely%20intervention%2C%20and%20guide%20personalized%20care.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%2C%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20Highlights%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20Speech%20is%20a%20promising%20digital%20marker%20for%20prognosis%20in%20AD%20due%20to%20its%20real%5Cu2010world%20feasibility%20and%20evidence%20of%20clinical%20utility.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20Speech%20offers%20a%20valuable%20complement%20to%20blood%20biomarkers%20for%20predicting%20future%20cognitive%20decline.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20Progress%20in%20developing%20speech%5Cu2010based%20tools%20has%20been%20constrained%20by%20the%20absence%20of%20large%2C%20longitudinal%2C%20and%20deeply%20phenotyped%20datasets.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20SpeechDx%20is%20a%203%5Cu2010year%2C%20multilingual%20observational%20study%20that%20will%20enable%20the%20development%20of%20diagnostic%20and%20prognostic%20tools%20for%20AD%20and%20related%20dementias.%22%2C%22date%22%3A%2206%5C%2F2026%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1002%5C%2Falz.71489%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Falz-journals.onlinelibrary.wiley.com%5C%2Fdoi%5C%2F10.1002%5C%2Falz.71489%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%221552-5260%2C%201552-5279%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222026-07-30T13%3A52%3A22Z%22%7D%7D%2C%7B%22key%22%3A%22M2RSWA2Z%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22He%20et%20al.%22%2C%22parsedDate%22%3A%222026%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BHe%2C%20L.%2C%20Li%2C%20H.%2C%20Wang%2C%20S.%2C%20Baik%2C%20E.%2C%20Kervin%2C%20S.%2C%20Zhao%2C%20R.%2C%20Ramos%2C%20J.%20M.%2C%20Bridge2AI%26%23x2010%3BVoice%20Consortium%2C%20Colonel%2C%20J.%2C%20%26amp%3B%20Rameau%2C%20A.%20%282026%29.%20Decoding%20Gender%20in%20Cough%20Sounds%3A%20A%20Transformer%26%23x2010%3BBased%20Analysis.%20%26lt%3Bi%26gt%3BThe%20Laryngoscope%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B136%26lt%3B%5C%2Fi%26gt%3B%286%29%2C%202519%26%23x2013%3B2527.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Flary.70393%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Flary.70393%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Decoding%20Gender%20in%20Cough%20Sounds%3A%20A%20Transformer%5Cu2010Based%20Analysis%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Linh%22%2C%22lastName%22%3A%22He%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Haomiao%22%2C%22lastName%22%3A%22Li%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Siyan%22%2C%22lastName%22%3A%22Wang%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Eunice%22%2C%22lastName%22%3A%22Baik%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sarah%22%2C%22lastName%22%3A%22Kervin%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Robin%22%2C%22lastName%22%3A%22Zhao%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22John%20M.%22%2C%22lastName%22%3A%22Ramos%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22Bridge2AI%5Cu2010Voice%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Joseph%22%2C%22lastName%22%3A%22Colonel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ana%5Cu00efs%22%2C%22lastName%22%3A%22Rameau%22%7D%5D%2C%22abstractNote%22%3A%22ABSTRACT%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Objective%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Various%20components%20of%20speech%2C%20such%20as%20pitch%2C%20volume%2C%20and%20resonance%2C%20influence%20gender%20perception%2C%20but%20little%20is%20known%20about%20gender%20differences%20in%20non%5Cu2010speech%20upper%20airway%20sounds%20such%20as%20cough.%20This%20gap%20has%20implications%20for%20gender%5Cu2010affirming%20voice%20care%2C%20as%20coughs%20are%20harder%20to%20modulate.%20We%20aimed%20to%20explore%20how%20cough%20acoustics%20differ%20by%20gender%20using%20a%20transformer%20model%20with%20self%5Cu2010attention%20to%20identify%20salient%20cough%20features%20for%20gender%20classification.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Methods%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20We%20analyzed%20327%20cough%20recordings%20%28154%20male%2C%20173%20female%29%20from%20the%20Coswara%20dataset%2C%20using%20a%2070%5C%2F15%5C%2F15%20split%20for%20model%20training%2C%20validation%2C%20and%20testing.%20Preprocessing%20included%20resampling%2C%20silence%20removal%2C%20normalization%2C%20and%20trimming%20to%20uniform%20length.%20The%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20HuBERT%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20transformer%20model%20was%20used%20for%20its%20ability%20to%20handle%20unstructured%20audio.%20Gender%20balance%20was%20verified%20through%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20SMD%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%28standardized%20mean%20difference%29%20screening%20across%20seven%20variables%2C%20all%20of%20which%20showed%20negligible%20imbalance.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Results%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20On%20the%20held%5Cu2010out%20test%20set%2C%20the%20model%20achieved%20an%20accuracy%20of%2084.0%25%20with%20an%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20F1%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20score%20of%200.8462%20when%20classifying%20gender%20from%20cough%20series%2C%20compared%20to%2071.4%25%20accuracy%20and%20an%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20F1%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20score%20of%200.7308%20when%20using%20single%5Cu2010cough%5C%2Ffirst%5Cu2010cough%20samples.%20Attention%5Cu2010aligned%20cough%20visualization%20revealed%20the%20highest%20attention%20on%20the%20explosive%20phases%20of%20the%20cough%2C%20suggesting%20that%20these%20segments%20encapsulate%20the%20most%20salient%20gender%5Cu2010distinct%20acoustic%20cues.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Conclusion%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Cough%20sounds%20contain%20gender%5Cu2010discriminative%20features%20detectable%20by%20transformer%20models.%20Attention%20to%20specific%20cough%20phases%20reveals%20physiologically%20meaningful%20segments%20in%20cough%20sounds%20supporting%20gender%20classification.%20These%20insights%20may%20inform%20gender%5Cu2010affirming%20interventions%2C%20particularly%20for%20non%5Cu2010speech%20sound%20production.%20Future%20research%20should%20explore%20further%20socio%5Cu2010demographic%20factors%20shaping%20cough%20acoustics.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Level%20of%20Evidence%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%204.%22%2C%22date%22%3A%2206%5C%2F2026%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1002%5C%2Flary.70393%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fonlinelibrary.wiley.com%5C%2Fdoi%5C%2F10.1002%5C%2Flary.70393%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%220023-852X%2C%201531-4995%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222026-07-30T13%3A45%3A20Z%22%7D%7D%2C%7B%22key%22%3A%22FRKHY2ST%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Piao%20et%20al.%22%2C%22parsedDate%22%3A%222025-12-19%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BPiao%2C%20R.%2C%20Lu%2C%20Y.%2C%20Kemps%2C%20H.%2C%20Xia%2C%20T.%2C%20%26amp%3B%20Saeed%2C%20A.%20%282025%29.%20%26lt%3Bi%26gt%3BUnified%20Acoustic%20Representations%20for%20Screening%20Neurological%20and%20Respiratory%20Pathologies%20from%20Voice%26lt%3B%5C%2Fi%26gt%3B%20%28arXiv%3A2508.20717%29.%20arXiv.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.48550%5C%2FarXiv.2508.20717%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.48550%5C%2FarXiv.2508.20717%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22preprint%22%2C%22title%22%3A%22Unified%20Acoustic%20Representations%20for%20Screening%20Neurological%20and%20Respiratory%20Pathologies%20from%20Voice%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ran%22%2C%22lastName%22%3A%22Piao%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yuan%22%2C%22lastName%22%3A%22Lu%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hareld%22%2C%22lastName%22%3A%22Kemps%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tong%22%2C%22lastName%22%3A%22Xia%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Aaqib%22%2C%22lastName%22%3A%22Saeed%22%7D%5D%2C%22abstractNote%22%3A%22Voice-based%20health%20assessment%20offers%20unprecedented%20opportunities%20for%20scalable%2C%20non-invasive%20disease%20screening%2C%20yet%20existing%20approaches%20typically%20focus%20on%20single%20conditions%20and%20fail%20to%20leverage%20the%20rich%2C%20multi-faceted%20information%20embedded%20in%20speech.%20We%20present%20MARVEL%20%28Multi-task%20Acoustic%20Representations%20for%20Voice-based%20Health%20Analysis%29%2C%20a%20privacy-conscious%20multitask%20learning%20framework%20that%20simultaneously%20detects%20nine%20distinct%20neurological%2C%20respiratory%2C%20and%20voice%20disorders%20using%20only%20derived%20acoustic%20features%2C%20eliminating%20the%20need%20for%20raw%20audio%20transmission.%20Our%20dual-branch%20architecture%20employs%20specialized%20encoders%20with%20task-specific%20heads%20sharing%20a%20common%20acoustic%20backbone%2C%20enabling%20effective%20cross-condition%20knowledge%20transfer.%20Evaluated%20on%20the%20large-scale%20Bridge2AI-Voice%20v2.0%20dataset%2C%20MARVEL%20achieves%20an%20overall%20AUROC%20of%200.78%2C%20with%20exceptional%20performance%20on%20neurological%20disorders%20%28AUROC%20%3D%200.89%29%2C%20particularly%20for%20Alzheimer%26%23039%3Bs%20disease%5C%2Fmild%20cognitive%20impairment%20%28AUROC%20%3D%200.97%29.%20Our%20framework%20consistently%20outperforms%20single-modal%20baselines%20by%205-19%25%20and%20surpasses%20state-of-the-art%20self-supervised%20models%20on%207%20of%209%20tasks%2C%20while%20correlation%20analysis%20reveals%20that%20the%20learned%20representations%20exhibit%20meaningful%20similarities%20with%20established%20acoustic%20features%2C%20indicating%20that%20the%20model%26%23039%3Bs%20internal%20representations%20are%20consistent%20with%20clinically%20recognized%20acoustic%20patterns.%20By%20demonstrating%20that%20a%20single%20unified%20model%20can%20effectively%20screen%20for%20diverse%20conditions%2C%20this%20work%20establishes%20a%20foundation%20for%20deployable%20voice-based%20diagnostics%20in%20resource-constrained%20and%20remote%20healthcare%20settings.%22%2C%22genre%22%3A%22%22%2C%22repository%22%3A%22arXiv%22%2C%22archiveID%22%3A%22arXiv%3A2508.20717%22%2C%22date%22%3A%222025-12-19%22%2C%22DOI%22%3A%2210.48550%5C%2FarXiv.2508.20717%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22http%3A%5C%2F%5C%2Farxiv.org%5C%2Fabs%5C%2F2508.20717%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222026-07-30T13%3A45%3A56Z%22%7D%7D%2C%7B%22key%22%3A%222FHLSWKB%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Pizzimenti%20et%20al.%22%2C%22parsedDate%22%3A%222025-12-03%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BPizzimenti%2C%20M.%2C%20Kalia%2C%20A.%2C%20Toghranegar%2C%20J.%20A.%2C%20Ebraheem%2C%20M.%2C%20Cummins%2C%20N.%2C%20Ghosh%2C%20S.%20S.%2C%20Anibal%2C%20J.%20T.%2C%20Au%2C%20R.%2C%20Azarang%2C%20A.%2C%20Bahr%2C%20R.%20H.%2C%20Bedrick%2C%20S.%20D.%2C%20Botha%2C%20H.%2C%20Coleman%2C%20O.%20C.%2C%20Elbeji%2C%20A.%2C%20Kourtis%2C%20L.%20C.%2C%20Rameau%2C%20A.%2C%20Sara%2C%20J.%20D.%20S.%2C%20Watts%2C%20S.%20W.%2C%20Hemmerling%2C%20D.%2C%20%26%23x2026%3B%20Fagherazzi%2C%20G.%20%282025%29.%20%26lt%3Bi%26gt%3BConsensus-Based%20Definitions%20for%20Vocal%20Biomarkers%3A%20The%20International%20VOCAL%20Initiative%26lt%3B%5C%2Fi%26gt%3B.%20medRxiv.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1101%5C%2F2025.10.23.25338518%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1101%5C%2F2025.10.23.25338518%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22preprint%22%2C%22title%22%3A%22Consensus-Based%20Definitions%20for%20Vocal%20Biomarkers%3A%20The%20International%20VOCAL%20Initiative%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22M%5Cu00e9gane%22%2C%22lastName%22%3A%22Pizzimenti%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ayush%22%2C%22lastName%22%3A%22Kalia%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jamie%20A.%22%2C%22lastName%22%3A%22Toghranegar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mohamed%22%2C%22lastName%22%3A%22Ebraheem%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nicholas%22%2C%22lastName%22%3A%22Cummins%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Satrajit%20S.%22%2C%22lastName%22%3A%22Ghosh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22James%20T.%22%2C%22lastName%22%3A%22Anibal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rhoda%22%2C%22lastName%22%3A%22Au%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Arian%22%2C%22lastName%22%3A%22Azarang%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ruth%20H.%22%2C%22lastName%22%3A%22Bahr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%20D.%22%2C%22lastName%22%3A%22Bedrick%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hugo%22%2C%22lastName%22%3A%22Botha%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Oita%20C.%22%2C%22lastName%22%3A%22Coleman%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Abir%22%2C%22lastName%22%3A%22Elbeji%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lampros%20C.%22%2C%22lastName%22%3A%22Kourtis%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ana%5Cu00efs%22%2C%22lastName%22%3A%22Rameau%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jaskanwal%20Deep%20Singh%22%2C%22lastName%22%3A%22Sara%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stephanie%20W.%22%2C%22lastName%22%3A%22Watts%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Daria%22%2C%22lastName%22%3A%22Hemmerling%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jiri%22%2C%22lastName%22%3A%22Mekyska%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Marisha%20L.%22%2C%22lastName%22%3A%22Speights%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22the%20Bridge2AI%20Voice%22%2C%22lastName%22%3A%22Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22the%20eVoiceNet%20COST%22%2C%22lastName%22%3A%22Action%20%28CA24128%29%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Christophe%22%2C%22lastName%22%3A%22B%5Cu00e9lisle-Pipon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%20E.%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Guy%22%2C%22lastName%22%3A%22Fagherazzi%22%7D%5D%2C%22abstractNote%22%3A%22Importance%20Voice-based%20health%20technologies%20are%20growing%20rapidly%2C%20but%20they%20lack%20standardized%20terminology%2C%20which%20hinders%20interdisciplinary%20collaboration%2C%20research%20quality%2C%20and%20clinical%20translation.%5CnObjective%20The%20objective%20of%20this%20work%20is%20to%20develop%20universally%20accepted%20definitions%20in%20the%20rapidly%20evolving%20field%20of%20vocal%20biomarkers%2C%20as%20part%20of%20the%20VOCAL%20%28Vocal%20Biomarker%20Guidelines%20for%20Ontology%2C%20Classification%2C%20Application%2C%20and%20Logistics%29%20initiative%2C%20a%20structured%2C%20international%20consensus-based%20framework%20that%20aims%20to%20provide%20standards%2C%20and%20guidelines.%5CnDesign%20VOCAL%20is%20a%20rigorous%2C%20international%2C%20multi-stage%20consensus-building%20study%20conducted%20in%202024-2025.%5CnSetting%20Multi-institutional%20collaboration%20between%20representatives%20from%20the%20Bridge2AI-Voice%20Consortium%20%28North%20America%29%20and%20the%20eVoiceNet%20Network%20%28European%20Union%29%2C%20culminating%20in%20an%20in-person%20workshop%20at%20the%202025%20Bridge2AI%20Voice%20Symposium.%5CnParticipants%20A%20group%20of%2024%20international%20experts%20in%20medicine%2C%20clinical%20research%2C%20speech%20and%20language%2C%20audio%20signal%20processing%2C%20statistics%2C%20methodology%2C%20regulation%2C%20ethics.%5CnMethods%20VOCAL%5Cu2019s%20iterative%20process%20involved%20five%20rounds%20of%20review%2C%20feedback%2C%20and%20an%20in-person%20workshop%20at%20the%20international%202025%20Bridge2AI%20Voice%20Symposium%2C%20ensuring%20the%20incorporation%20of%20diverse%20perspectives%20and%20achieving%20a%20robust%20agreement%20on%20the%20proposed%20definitions.%5CnMain%20outcomes%20and%20measures%20Consensus-based%20definitions%20for%20vocal%20biomarkers%2C%20spanning%20from%20broad%20concepts%20%28biomarker%2C%20digital%20biomarker%2C%20vocal%20biomarker%29%20to%20domain-specific%20measures%20%28cardio-respiratory%20acoustic%2C%20voice%2C%20speech%5C%2Farticulatory%2C%20cognitive%5C%2Flanguage%29.%5CnResults%20A%20hierarchical%20continuum%20model%20of%20vocal%20biomarkers%20was%20established.%20We%20first%20distinguished%20between%20the%20concepts%20of%20vocal%20measures%20and%20vocal%20biomarkers.%20We%20then%20defined%20terms%20from%20broad%2C%20overarching%20concepts%20%28Level%200%3A%20Biomarker%2C%20Digital%20Biomarker%2C%20Vocal%20Biomarker%29%20to%20more%20specific%20physiological%20and%20cognitive%20domains%20%28Level%201%3A%20Cardio-Respiratory%20Acoustic%3B%20Level%202%3A%20Voice%3B%20Level%203%3A%20Speech%5C%2FArticulatory%3B%20Level%204%3A%20Cognitive%5C%2FLanguage%2C%20including%20linguistic%20and%20paralinguistic%20subtypes%29.%5CnConclusions%20and%20Relevance%20This%20work%20provides%20a%20shared%20vocabulary%20that%20is%20essential%20for%20fostering%20communication%20through%20interdisciplinary%20collaboration%2C%20improving%20the%20quality%20and%20efficiency%20of%20research%20and%20development%2C%20and%20ensuring%20the%20ethical%2C%20reliable%2C%20and%20scalable%20deployment%20of%20future%20voice-based%20health%20technologies.%20It%20lays%20foundational%20groundwork%20for%20upcoming%20guidelines%20and%20standards%2C%20which%20are%20crucial%20for%20advancing%20the%20field%20of%20vocal%20biomarkers%20into%20widespread%20clinical%20utility.%5CnQuestion%20Can%20we%20establish%20an%20international%20consensus%20on%20the%20definitions%20related%20to%20vocal%20biomarkers%3FFindings%20Through%20a%20multi-stage%20international%20consensus%20process%20involving%20expert%20representatives%20from%20the%20Bridge2AI-Voice%20Consortium%20and%20eVoiceNet%20Network%2C%20a%20hierarchical%20model%20of%20vocal%20biomarkers%20was%20developed%2C%20defining%20terms%20from%20broad%20concepts%20%28biomarker%2C%20digital%20biomarker%2C%20vocal%20biomarker%29%20to%20specific%20physiological%20and%20cognitive%20domains%20%28cardio-respiratory%20acoustic%2C%20voice%2C%20speech%5C%2Farticulatory%2C%20cognitive%5C%2Flanguage%29.Meaning%20Standardized%20definitions%20for%20vocal%20biomarkers%20provide%20an%20essential%20shared%20vocabulary%20for%20interdisciplinary%20collaboration%20and%20lay%20the%20foundational%20groundwork%20for%20future%20guidelines%20needed%20to%20advance%20the%20implementation%20of%20voice-based%20health%20technologies%20into%20clinical%20practice%20and%20clinical%20research.%22%2C%22genre%22%3A%22%22%2C%22repository%22%3A%22medRxiv%22%2C%22archiveID%22%3A%22%22%2C%22date%22%3A%222025-12-03%22%2C%22DOI%22%3A%2210.1101%5C%2F2025.10.23.25338518%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.medrxiv.org%5C%2Fcontent%5C%2F10.1101%5C%2F2025.10.23.25338518v2%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222025-12-11T14%3A15%3A09Z%22%7D%7D%2C%7B%22key%22%3A%22LM4XXTC5%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Miao%20et%20al.%22%2C%22parsedDate%22%3A%222025-12-01%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BMiao%2C%20S.%2C%20Choi%2C%20J.%2C%20Russell%2C%20L.%2C%20Bensoussan%2C%20Y.%2C%20Ng%2C%20E.%2C%20Johnson%2C%20A.%2C%20Wolter%2C%20N.%20E.%2C%20Propst%2C%20E.%20J.%2C%20%26amp%3B%20Siu%2C%20J.%20M.%20%282025%29.%20Feasibility%20of%20a%20Pediatric%20Voice%20Protocol%20for%20Artificial%20Intelligence%20Research.%20%26lt%3Bi%26gt%3BJournal%20of%20Voice%26lt%3B%5C%2Fi%26gt%3B.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.jvoice.2025.10.010%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.jvoice.2025.10.010%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Feasibility%20of%20a%20Pediatric%20Voice%20Protocol%20for%20Artificial%20Intelligence%20Research%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Siyu%22%2C%22lastName%22%3A%22Miao%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jinny%22%2C%22lastName%22%3A%22Choi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Laurie%22%2C%22lastName%22%3A%22Russell%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Evan%22%2C%22lastName%22%3A%22Ng%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alistair%22%2C%22lastName%22%3A%22Johnson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nikolaus%20E.%22%2C%22lastName%22%3A%22Wolter%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Evan%20J.%22%2C%22lastName%22%3A%22Propst%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jennifer%20M.%22%2C%22lastName%22%3A%22Siu%22%7D%5D%2C%22abstractNote%22%3A%22Introduction%5CnThere%20is%20increasing%20interest%20in%20leveraging%20artificial%20intelligence%20%28AI%29%20research%20in%20voice%20for%20pediatric%20healthcare.%20However%2C%20creating%20high-quality%20databases%20for%20pediatric%20voice%20AI%20research%20presents%20unique%20challenges%20due%20to%20developmental%20differences%20in%20attention%20and%20adherence.%20Effective%20data%20collection%20methods%20must%20accommodate%20age-specific%20needs%20while%20ensuring%20consistency%20in%20recording%20conditions%20and%20feasibility%20across%20diverse%20age%20groups.%20Research%20on%20standardized%20approaches%20for%20capturing%20pediatric%20voice%20data%20in%20clinical%20settings%20remains%20limited.%5CnMethods%5CnThis%20prospective%20observational%20study%20incorporated%20demographic%20surveys%20and%20validated%20questionnaires%20to%20collect%20medical%20and%20demographic%20data%2C%20alongside%20voice%20acoustic%20tasks%20grouped%20into%20four%20age-based%20categories.%20Data%20collection%20was%20conducted%20using%20two%20iPads%20with%20headphones.%20The%20primary%20outcome%20was%20protocol%20feasibility%2C%20encompassing%20proportions%20of%20successful%20task%20completion%2C%20headphones%20usage%2C%20required%20prompting%2C%20and%20average%20length%20of%20time%20to%20complete%20the%20full%20assessment.%20Secondary%20outcomes%20were%20the%20fundamental%20frequency%20%28Hz%29%2C%20jitter%20%28%25%29%2C%20shimmer%20%28%25%29%2C%20and%20harmonic-to-noise%20ratio%20%28dB%29%20of%20the%20recordings%20to%20measure%20acoustic%20quality.%5CnResults%5CnHundred%20participants%20were%20recruited%20%2850%20females%2C%2050%20males%29%20from%20a%20tertiary%20care%20otolaryngology%20clinic%20at%20the%20Hospital%20for%20Sick%20Children%20between%20October%202024%20and%20January%202025.%20The%20majority%20%2875%25%29%20completed%20the%20assessment%20within%2010%5Cu201325%5Cu00a0minutes%2C%20while%20a%20smaller%20proportion%20required%20additional%20time%20due%20to%20young%20age%20or%20medical%20complexity.%20Headphone%20compliance%20was%20high%20%2890%25%29%2C%20with%20alternative%20methods%20to%20ensure%20data%20continuity.%20Younger%20participants%20required%20more%20prompting%2C%20and%20male%20participants%20in%20younger%20age%20groups%20were%20less%20likely%20to%20tolerate%20headphones.%20Acoustic%20measures%20were%20consistent%20with%20published%20age-%20and%20sex-%20based%20norms.%5CnConclusion%5CnThis%20study%20demonstrates%20the%20feasibility%20of%20collecting%20acoustic%20data%20to%20support%20AI%20research%20in%20pediatric%20populations.%20Addressing%20age-specific%20needs%20and%20parental%20concerns%20is%20critical%20for%20optimizing%20engagement%20and%20ensuring%20high-quality%20datasets.%20These%20findings%20provide%20valuable%20insights%20for%20improving%20recruitment%2C%20adherence%2C%20and%20data%20integrity%2C%20contributing%20to%20the%20creation%20of%20robust%20pediatric%20voice%20AI%20databases%20for%20future%20clinical%20and%20research%20applications.%22%2C%22date%22%3A%222025-12-01%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.jvoice.2025.10.010%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.sciencedirect.com%5C%2Fscience%5C%2Farticle%5C%2Fpii%5C%2FS0892199725004229%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%220892-1997%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222025-12-11T14%3A13%3A50Z%22%7D%7D%2C%7B%22key%22%3A%22KHBFMNV3%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Mahapatra%20and%20Mahapatra%22%2C%22parsedDate%22%3A%222025-11-27%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BMahapatra%2C%20I.%2C%20%26amp%3B%20Mahapatra%2C%20N.%20R.%20%282025%2C%20November%2027%29.%20%26lt%3Bi%26gt%3BFAIR%20Voice%20Biomarker%20Data%20for%20Safe-Assured%20Embodied%20Health%20AI%26lt%3B%5C%2Fi%26gt%3B.%20Embodied%20and%20Safe-Assured%20Robotic%20Systems.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fopenreview.net%5C%2Fforum%3Fid%3DL3VxhW2KWh%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fopenreview.net%5C%2Fforum%3Fid%3DL3VxhW2KWh%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22conferencePaper%22%2C%22title%22%3A%22FAIR%20Voice%20Biomarker%20Data%20for%20Safe-Assured%20Embodied%20Health%20AI%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ishaan%22%2C%22lastName%22%3A%22Mahapatra%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nihar%20R.%22%2C%22lastName%22%3A%22Mahapatra%22%7D%5D%2C%22abstractNote%22%3A%22Voice-based%20signals%20such%20as%20speech%2C%20breathing%2C%20and%20coughing%20form%20a%20primary%20perceptual%20channel%20for%20embodied%20health%20AI%20systems%5Cu2014from%20assistive%20robots%20and%20diagnostic%20companions%20to%20multimodal%20therapeutic%20agents.%20The%20safety%20and%20trustworthiness%20of%20such%20systems%20depend%20not%20only%20on%20model%20behavior%20but%20on%20the%20quality%2C%20traceability%2C%20and%20interoperability%20of%20the%20sensory%20data%20that%20drive%20their%20perception.%20Yet%2C%20current%20voice%20biomarker%20resources%20exhibit%20uneven%20data%20governance%20and%20limited%20adherence%20to%20the%20FAIR%20principles%5Cu2014Findability%2C%20Accessibility%2C%20Interoperability%2C%20and%20Reusability%5Cu2014creating%20hidden%20risks%20for%20safety%20assurance%20and%20regulatory%20compliance.%20In%20this%20work%2C%20we%20perform%20a%20comprehensive%20FAIRness%20evaluation%20of%20publicly%20available%20voice%20biomarker%20datasets%20spanning%20five%20major%20disease%20domains.%20Using%20a%20priority-weighted%20rubric%20aligned%20with%20the%20FAIR%20Data%20Maturity%20Model%2C%20we%20benchmark%20expert%20manual%20assessments%20against%20three%20automated%20tools%20%28F-UJI%2C%20FAIR%20Evaluator%2C%20and%20FAIR-Checker%29%20and%20quantify%20agreement%20and%20reliability%20through%20human%5Cu2013tool%20comparison%20and%20test%5Cu2013retest%20analysis.%20Results%20reveal%20strong%20Findability%20and%20Accessibility%20but%20persistent%20weaknesses%20in%20Interoperability%20and%20Reusability%2C%20notably%20in%20controlled%20vocabularies%2C%20qualified%20references%2C%20licensing%2C%20and%20provenance%5Cu2014elements%20essential%20for%20traceable%20and%20verifiable%20embodied%20perception%20pipelines.%20Automated%20tools%20often%20underestimated%20compliance%20due%20to%20rigid%2C%20domain-agnostic%20logic%2C%20underscoring%20the%20need%20for%20contextual%20evaluation.%20We%20introduce%20a%20data-level%20safety-assurance%20perspective%2C%20positioning%20FAIRness%20as%20a%20foundation%20for%20verifiable%2C%20policy-aligned%20embodied%20AI.%20By%20providing%20actionable%20recommendations%5Cu2014domain-specific%20metadata%20standards%2C%20machine-readable%20licensing%2C%20and%20FAIR-supportive%20repositories%5Cu2014we%20outline%20a%20practical%20pathway%20toward%20trustworthy%2C%20reproducible%2C%20and%20safe-assured%20embodied%20health%20AI%20systems.%22%2C%22proceedingsTitle%22%3A%22%22%2C%22conferenceName%22%3A%22Embodied%20and%20Safe-Assured%20Robotic%20Systems%22%2C%22date%22%3A%222025%5C%2F11%5C%2F27%22%2C%22eventPlace%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22ISBN%22%3A%22%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fopenreview.net%5C%2Fforum%3Fid%3DL3VxhW2KWh%22%2C%22ISSN%22%3A%22%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%22IHZBBNUB%22%5D%2C%22dateModified%22%3A%222025-12-11T14%3A17%3A36Z%22%7D%7D%2C%7B%22key%22%3A%22RN7FNVSN%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Dorr%20et%20al.%22%2C%22parsedDate%22%3A%222025-10-21%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BDorr%2C%20D.%20A.%2C%20Krussel%2C%20A.%2C%20Hauck%2C%20R.%2C%20Jackson%2C%20C.%2C%20Dalal%2C%20A.%2C%20Bedrick%2C%20S.%2C%20Payne%2C%20P.%20R.%20O.%2C%20Bridge2AI-Voice%20Consortium%2C%20Hersh%2C%20W.%2C%20Bensoussan%2C%20Y.%2C%20Elemento%2C%20O.%2C%20Rameau%2C%20A.%2C%20Sigaras%2C%20A.%2C%20Ghosh%2C%20S.%2C%20Powell%2C%20M.%2C%20Ravitsky%2C%20V.%2C%20Christophe%20Belisle-Pipon%2C%20J.%2C%20Dorr%2C%20D.%2C%20Payne%2C%20P.%2C%20%26%23x2026%3B%20Goldenberg%2C%20A.%20%282025%29.%20Adapting%20data%20science%20competencies%20by%20role%20and%20purpose%3A%20Voice%20AI.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Digital%20Health%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B7%26lt%3B%5C%2Fi%26gt%3B.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2025.1610253%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2025.1610253%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Adapting%20data%20science%20competencies%20by%20role%20and%20purpose%3A%20Voice%20AI%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%20A.%22%2C%22lastName%22%3A%22Dorr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andrea%22%2C%22lastName%22%3A%22Krussel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rachel%22%2C%22lastName%22%3A%22Hauck%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christie%22%2C%22lastName%22%3A%22Jackson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Abhijeet%22%2C%22lastName%22%3A%22Dalal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Bedrick%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Philip%20R.%20O.%22%2C%22lastName%22%3A%22Payne%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22%22%2C%22lastName%22%3A%22Bridge2AI-Voice%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22William%22%2C%22lastName%22%3A%22Hersh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Olivier%22%2C%22lastName%22%3A%22Elemento%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anais%22%2C%22lastName%22%3A%22Rameau%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexandros%22%2C%22lastName%22%3A%22Sigaras%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Satrajit%22%2C%22lastName%22%3A%22Ghosh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maria%22%2C%22lastName%22%3A%22Powell%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Vardit%22%2C%22lastName%22%3A%22Ravitsky%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean%22%2C%22lastName%22%3A%22Christophe%20Belisle-Pipon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Dorr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Phillip%22%2C%22lastName%22%3A%22Payne%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alistair%22%2C%22lastName%22%3A%22Johnson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ruth%22%2C%22lastName%22%3A%22Bahr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Donald%22%2C%22lastName%22%3A%22Bolser%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Frank%22%2C%22lastName%22%3A%22Rudzicz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jordan%22%2C%22lastName%22%3A%22Lerner-Ellis%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Kathy%22%2C%22lastName%22%3A%22Jenkins%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shaheen%22%2C%22lastName%22%3A%22Awan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Micah%22%2C%22lastName%22%3A%22Boyer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22William%22%2C%22lastName%22%3A%22Hersh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andrea%22%2C%22lastName%22%3A%22Krussel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Bedrick%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Toufeeq%22%2C%22lastName%22%3A%22Ahmed%20Syed%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jamie%22%2C%22lastName%22%3A%22Toghranegar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22James%22%2C%22lastName%22%3A%22Anibal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Duncan%22%2C%22lastName%22%3A%22Sutherland%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Enrique%22%2C%22lastName%22%3A%22Diaz-Ocampo%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22John%22%2C%22lastName%22%3A%22Costello%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexander%22%2C%22lastName%22%3A%22Gelbard%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Kimberly%22%2C%22lastName%22%3A%22Vinson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tempestt%22%2C%22lastName%22%3A%22Neal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lochana%22%2C%22lastName%22%3A%22Jayachandran%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Evan%22%2C%22lastName%22%3A%22Ng%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Selina%22%2C%22lastName%22%3A%22Casalino%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yassmeen%22%2C%22lastName%22%3A%22Abdel-Aty%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Karim%22%2C%22lastName%22%3A%22Hanna%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Theresa%22%2C%22lastName%22%3A%22Zesiewicz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Elijah%22%2C%22lastName%22%3A%22Moothedan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Emily%22%2C%22lastName%22%3A%22Evangelista%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Samantha%22%2C%22lastName%22%3A%22Salvi%20Cruz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Robin%22%2C%22lastName%22%3A%22Zhao%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mohamed%22%2C%22lastName%22%3A%22Ebraheem%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Karlee%22%2C%22lastName%22%3A%22Newberry%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Iris%22%2C%22lastName%22%3A%22De%20Santiago%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ellie%22%2C%22lastName%22%3A%22Eiseman%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22J.%20M.%22%2C%22lastName%22%3A%22Rahman%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stacy%22%2C%22lastName%22%3A%22Jo%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anna%22%2C%22lastName%22%3A%22Goldenberg%22%7D%5D%2C%22abstractNote%22%3A%22Competencies%20help%20define%20the%20skills%20and%20knowledge%20needed%20by%20learners.%20Often%20broad%2C%20educators%20integrate%20competencies%20to%20provide%20a%20framework%20for%20curricula%20or%20professional%20standards.%20For%20data%20science%2C%20the%20rate%20of%20change%20in%20the%20field%2C%20role%20variations%2C%20and%20specificity%20in%20key%20applications%20can%20be%20challenging.%20Our%20objective%20was%20to%20adapt%20general%20data%20science%20competencies%20for%20different%20learner%20roles%20in%20an%20emerging%20area%3A%20the%20clinical%20utility%20of%20Voice%2C%20Language%2C%20and%20Speech-based%20Artificial%20Intelligence%5C%2FMachine%20Learning%20%28AI%5C%2FML%29.%20Using%20a%20persona-inductive%20approach%2C%20we%20adapted%20competencies%20to%20support%20learners%20from%20varying%20professional%20and%20educational%20backgrounds%20and%20implemented%20these%20adaptations%20in%20a%20multi-institutional%20summer%20school.%20Results%20from%20these%20pilot%20efforts%20demonstrated%20feasibility%2C%20highlighted%20the%20importance%20of%20cross-role%20collaboration%2C%20and%20provided%20lessons%20for%20scaling%20to%20broader%20audiences.%20Our%20frameworks%20show%20that%20competency%20adaptation%20is%20necessary%20and%20practical%20in%20rapidly%20evolving%20AI%20domains.%22%2C%22date%22%3A%222025-10-21%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffdgth.2025.1610253%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Fjournals%5C%2Fdigital-health%5C%2Farticles%5C%2F10.3389%5C%2Ffdgth.2025.1610253%5C%2Ffull%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-253X%22%2C%22language%22%3A%22English%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222025-12-11T14%3A14%3A18Z%22%7D%7D%2C%7B%22key%22%3A%22MF7GHZRR%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Gallois%20et%20al.%22%2C%22parsedDate%22%3A%222025-10-15%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BGallois%2C%20H.%2C%20Ivkovic%2C%20L.%2C%20Evangelista%2C%20E.%2C%20Bensoussan%2C%20Y.%2C%20Dorr%2C%20D.%20A.%2C%20Elemento%2C%20O.%2C%20Ghosh%2C%20S.%20S.%2C%20Johnson%2C%20A.%2C%20Payne%2C%20P.%2C%20Powell%2C%20M.%20E.%2C%20Rameau%2C%20A.%2C%20Ravitsky%2C%20V.%2C%20Sigaras%2C%20A.%2C%20B%26%23xE9%3Blisle-Pipon%2C%20J.-C.%2C%20%26amp%3B%20B2AI-Voice%20Consortium.%20%282025%29.%20%26%23x201C%3BLow%20Risk%2C%20High%20Happiness%26%23x201D%3B%3A%20A%20Review%20of%20Openly%20Declared%20Ethical%20and%20Legal%20Practices%20in%20Voice%20Biomarker%20Health-Tech%20Start-Ups.%20%26lt%3Bi%26gt%3BHealth%20Care%20Analysis%26lt%3B%5C%2Fi%26gt%3B.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs10728-025-00539-w%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs10728-025-00539-w%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22%5Cu201cLow%20Risk%2C%20High%20Happiness%5Cu201d%3A%20A%20Review%20of%20Openly%20Declared%20Ethical%20and%20Legal%20Practices%20in%20Voice%20Biomarker%20Health-Tech%20Start-Ups%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hortense%22%2C%22lastName%22%3A%22Gallois%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Luka%22%2C%22lastName%22%3A%22Ivkovic%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Emily%22%2C%22lastName%22%3A%22Evangelista%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%20A.%22%2C%22lastName%22%3A%22Dorr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Olivier%22%2C%22lastName%22%3A%22Elemento%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Satrajit%20S.%22%2C%22lastName%22%3A%22Ghosh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alistair%22%2C%22lastName%22%3A%22Johnson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Philip%22%2C%22lastName%22%3A%22Payne%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maria%20Ellen%22%2C%22lastName%22%3A%22Powell%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anais%22%2C%22lastName%22%3A%22Rameau%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Vardit%22%2C%22lastName%22%3A%22Ravitsky%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexandros%22%2C%22lastName%22%3A%22Sigaras%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Christophe%22%2C%22lastName%22%3A%22B%5Cu00e9lisle-Pipon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22B2AI-Voice%20Consortium%22%7D%5D%2C%22abstractNote%22%3A%22Voice%20biomarker%20research%20is%20fueling%20a%20growing%20health-tech%20market%2C%20largely%20driven%20by%20start-ups.%20Yet%2C%20there%20is%20limited%20scholarship%20on%20how%20start-ups%20navigate%20the%20legal%20uncertainty%20surrounding%20voice%20data%20protection%20and%20the%20rising%20expectations%20for%20responsible%20AI.%20This%20study%20reviews%20the%20ethical%2C%20legal%20and%20regulatory%20practices%20as%20stated%20on%20the%20websites%20of%2027%20start-ups%20using%20voice%20as%20a%20biomarker%20in%20health-tech.%20The%20review%20reveals%20substantial%20disparities%20in%20the%20availability%2C%20readability%20and%20content%20of%20the%20information%20disclosed%2C%20especially%20regarding%20privacy%20policies%2C%20with%20only%20a%20few%20websites%20offering%20product-specific%2C%20transparent%2C%20and%20comprehensive%20privacy%20policies.%20Significant%20differences%20also%20emerged%20in%20the%20start-ups%5Cu2019%20terms%20of%20use%20and%20regulatory%20compliance%20statements%2C%20likely%20reflecting%20the%20novelty%20of%20the%20field%2C%20disparity%20in%20legal%20and%20regulatory%20requirements%2C%20and%20the%20absence%20of%20sector-specific%20ethical%20guidance.%20For%20example%2C%20while%20most%20start-ups%20reference%20compliance%20with%20data%20protection%20frameworks%20%28e.g.%2C%20HIPAA%2C%20GDPR%29%2C%20many%20fall%20short%20of%20best%20practices%20for%20transparency%2C%20accountability%2C%20and%20user-centered%20communication.%20We%20argue%20that%20the%20success%20of%20start-ups%20in%20health-tech%20depends%20on%20their%20capacity%20to%20capture%20and%20retain%20the%20attention%20of%20potential%20end-users%20and%20investors.%20By%20adopting%20accessible%2C%20transparent%20and%20forward-looking%20communication%20on%20how%20they%20frame%20their%20legal%20and%20ethical%20responsibilities%20in%20practice%2C%20start-ups%20can%20not%20only%20ensure%20legal%20and%20regulatory%20compliance%20but%20build%20trust%20and%20support%20sustainable%20innovation.%20This%20work%20identifies%20key%20best%20practices%20for%20voice%20AI%20start-ups%20to%20consider%20and%20lays%20the%20foundation%20for%20future%20research%2C%20including%20surveys%20and%20longitudinal%20tracking%2C%20to%20better%20understand%20the%20evolving%20landscape%20of%20ethical%20and%20legal%20practices%20in%20voice%20biomarker%20and%20voice%20AI%20health-tech.%22%2C%22date%22%3A%222025-10-15%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1007%5C%2Fs10728-025-00539-w%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2Fs10728-025-00539-w%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%221573-3394%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222025-12-11T14%3A18%3A27Z%22%7D%7D%2C%7B%22key%22%3A%22RCZCJBUJ%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Caufield%20et%20al.%22%2C%22parsedDate%22%3A%222025-09-16%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BCaufield%2C%20H.%2C%20Ghosh%2C%20S.%2C%20Kong%2C%20S.%20W.%2C%20Parker%2C%20J.%2C%20Sheffield%2C%20N.%2C%20Patel%2C%20B.%2C%20Williams%2C%20A.%2C%20Clark%2C%20T.%2C%20%26amp%3B%20Munoz-Torres%2C%20M.%20C.%20%282025%29.%20%26lt%3Bi%26gt%3BStandards%20in%20the%20Preparation%20of%20Biomedical%20Research%20Metadata%3A%20A%20Bridge2AI%20Perspective%26lt%3B%5C%2Fi%26gt%3B%20%28arXiv%3A2509.10432%29.%20arXiv.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.48550%5C%2FarXiv.2509.10432%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.48550%5C%2FarXiv.2509.10432%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22preprint%22%2C%22title%22%3A%22Standards%20in%20the%20Preparation%20of%20Biomedical%20Research%20Metadata%3A%20A%20Bridge2AI%20Perspective%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Harry%22%2C%22lastName%22%3A%22Caufield%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Satrajit%22%2C%22lastName%22%3A%22Ghosh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sek%20Wong%22%2C%22lastName%22%3A%22Kong%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jillian%22%2C%22lastName%22%3A%22Parker%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nathan%22%2C%22lastName%22%3A%22Sheffield%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Bhavesh%22%2C%22lastName%22%3A%22Patel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andrew%22%2C%22lastName%22%3A%22Williams%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Timothy%22%2C%22lastName%22%3A%22Clark%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Monica%20C.%22%2C%22lastName%22%3A%22Munoz-Torres%22%7D%5D%2C%22abstractNote%22%3A%22AI-readiness%20describes%20the%20degree%20to%20which%20data%20may%20be%20optimally%20and%20ethically%20used%20for%20subsequent%20AI%20and%20Machine%20Learning%20%28AI%5C%2FML%29%20methods%2C%20where%20those%20methods%20may%20involve%20some%20combination%20of%20model%20training%2C%20data%20classification%2C%20and%20ethical%2C%20explainable%20prediction.%20The%20Bridge2AI%20consortium%20has%20defined%20the%20particular%20criteria%20a%20biomedical%20dataset%20may%20possess%20to%20render%20it%20AI-ready%3A%20in%20brief%2C%20a%20dataset%26%23039%3Bs%20readiness%20is%20related%20to%20its%20FAIRness%2C%20provenance%2C%20degree%20of%20characterization%2C%20explainability%2C%20sustainability%2C%20and%20computability%2C%20in%20addition%20to%20its%20accompaniment%20with%20documentation%20about%20ethical%20data%20practices.%20To%20ensure%20AI-readiness%20and%20to%20clarify%20data%20structure%20and%20relationships%20within%20Bridge2AI%26%23039%3Bs%20Grand%20Challenges%20%28GCs%29%2C%20particular%20types%20of%20metadata%20are%20necessary.%20The%20GCs%20within%20the%20Bridge2AI%20initiative%20include%20four%20data-generating%20projects%20focusing%20on%20generating%20AI%5C%2FML-ready%20datasets%20to%20tackle%20complex%20biomedical%20and%20behavioral%20research%20problems.%20These%20projects%20develop%20standardized%2C%20multimodal%20data%2C%20tools%2C%20and%20training%20resources%20to%20support%20AI%20integration%2C%20while%20addressing%20ethical%20data%20practices.%20Examples%20include%20using%20voice%20as%20a%20biomarker%2C%20building%20interpretable%20genomic%20tools%2C%20modeling%20disease%20trajectories%20with%20diverse%20multimodal%20data%2C%20and%20mapping%20cellular%20and%20molecular%20health%20indicators%20across%20the%20human%20body.%20This%20report%20assesses%20the%20state%20of%20metadata%20creation%20and%20standardization%20in%20the%20Bridge2AI%20GCs%2C%20provides%20guidelines%20where%20required%2C%20and%20identifies%20gaps%20and%20areas%20for%20improvement%20across%20the%20program.%20New%20projects%2C%20including%20those%20outside%20the%20Bridge2AI%20consortium%2C%20would%20benefit%20from%20what%20we%20have%20learned%20about%20creating%20metadata%20as%20part%20of%20efforts%20to%20promote%20AI%20readiness.%22%2C%22genre%22%3A%22%22%2C%22repository%22%3A%22arXiv%22%2C%22archiveID%22%3A%22arXiv%3A2509.10432%22%2C%22date%22%3A%222025-09-16%22%2C%22DOI%22%3A%2210.48550%5C%2FarXiv.2509.10432%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22http%3A%5C%2F%5C%2Farxiv.org%5C%2Fabs%5C%2F2509.10432%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222025-12-11T14%3A16%3A24Z%22%7D%7D%2C%7B%22key%22%3A%22RGDIAPIG%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Russell%20et%20al.%22%2C%22parsedDate%22%3A%222025-09-01%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BRussell%2C%20L.%2C%20Bensoussan%2C%20Y.%2C%20Ng%2C%20E.%2C%20Johnson%2C%20A.%2C%20Miao%2C%20S.%2C%20Wolter%2C%20N.%20E.%2C%20Propst%2C%20E.%20J.%2C%20%26amp%3B%20Siu%2C%20J.%20M.%20%282025%29.%20Developing%20age-specific%20protocols%20for%20pediatric%20voice%20databases%20in%20artificial%20intelligence%20research.%20%26lt%3Bi%26gt%3BInternational%20Journal%20of%20Pediatric%20Otorhinolaryngology%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B196%26lt%3B%5C%2Fi%26gt%3B%2C%20112455.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.ijporl.2025.112455%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.ijporl.2025.112455%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Developing%20age-specific%20protocols%20for%20pediatric%20voice%20databases%20in%20artificial%20intelligence%20research%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Laurie%22%2C%22lastName%22%3A%22Russell%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Evan%22%2C%22lastName%22%3A%22Ng%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Allistair%22%2C%22lastName%22%3A%22Johnson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Siyu%22%2C%22lastName%22%3A%22Miao%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nikolaus%20E.%22%2C%22lastName%22%3A%22Wolter%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Evan%20J.%22%2C%22lastName%22%3A%22Propst%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jennifer%20M.%22%2C%22lastName%22%3A%22Siu%22%7D%5D%2C%22abstractNote%22%3A%22Introduction%5CnChildren%26%23039%3Bs%20voice%20and%20communication%20abilities%20evolve%20with%20age%2C%20necessitating%20tailored%20protocols%20for%20accurate%20analysis.%20Distinct%20vocal%20properties%20and%20communication%20styles%20across%20developmental%20stages%20require%20specific%20tasks.%20The%20absence%20of%20standardized%20pediatric%20protocols%20impedes%20reliable%20voice%20data%20collection%2C%20limits%20robust%20acoustic%20measurements%2C%20and%20hinders%20AI-driven%20voice%20research.%20This%20study%20aims%20to%20develop%20age-specific%20voice%20data%20collection%20protocols%2C%20creating%20a%20pediatric%20voice%20database%20to%20advance%20research%20and%20enhance%20AI%20applications.%5CnMethods%5CnProtocols%20were%20developed%20iteratively%20over%20six%20months%20through%20a%20multidisciplinary%2C%20multi-institutional%20team%20involving%20speech-language%20pathologists%20and%20otolaryngologists.%20A%20comprehensive%20literature%20review%20was%20completed.%20Emphasis%20was%20placed%20on%20designing%20protocols%20capable%20of%20generating%20high-quality%2C%20consistent%20data%20for%20AI%20modeling%20while%20minimizing%20measurement%20variability.%5CnResults%5CnFour%20developmentally%20appropriate%20protocols%20were%20created%20for%20children%20aged%202%20to%20%26lt%3B4%20years%2C%204%20to%20%26lt%3B6%20years%2C%206%20to%20%26lt%3B10%20years%2C%20and%2010%2B%20years%20respectively.%20Each%20protocol%20targeted%20key%20acoustic%20parameters%20while%20aligning%20with%20the%20linguistic%20and%20cognitive%20abilities%20of%20the%20respective%20age%20group.%20The%20iterative%20design%20incorporated%20tasks%20that%20engaged%20children%20while%20ensuring%20clinically%20robust%20data%20collection.%20Standardized%20protocols%20were%20deployed%20via%20a%20user-friendly%20iPad%20application%2C%20using%20child-sized%20headset%20microphones%20at%20fixed%20distances%20from%20the%20mouth.%20The%20protocols%20were%20administered%20to%20100%20pediatric%20patients%20in%20an%20otolaryngology%20clinic%20between%20the%20ages%20of%202%5Cu201318.%5CnConclusions%5CnThe%20development%20of%20age%20specific%20protocols%20aims%20to%20standardize%20the%20collection%20of%20pediatric%20voice%20and%20acoustic%20sound%20data%2C%20which%20will%20serve%20as%20a%20valuable%20resource%20for%20advancing%20artificial%20intelligence%20applications%20within%20clinical%20sciences.%20Future%20validation%20will%20ensure%20feasibility%2C%20adherence%2C%20and%20reliability%20of%20data%20collection%20to%20support%20AI-driven%20innovations.%22%2C%22date%22%3A%222025-09-01%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.ijporl.2025.112455%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.sciencedirect.com%5C%2Fscience%5C%2Farticle%5C%2Fpii%5C%2FS0165587625002423%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%220165-5876%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222025-12-11T14%3A13%3A28Z%22%7D%7D%2C%7B%22key%22%3A%22P3UEDNRD%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Piao%20et%20al.%22%2C%22parsedDate%22%3A%222025-08-28%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BPiao%2C%20R.%2C%20Lu%2C%20Y.%2C%20Kemps%2C%20H.%2C%20Xia%2C%20T.%2C%20%26amp%3B%20Saeed%2C%20A.%20%282025%29.%20%26lt%3Bi%26gt%3BUnified%20Multi-task%20Learning%20for%20Voice-Based%20Detection%20of%20Diverse%20Clinical%20Conditions%26lt%3B%5C%2Fi%26gt%3B%20%28arXiv%3A2508.20717%29.%20arXiv.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.48550%5C%2FarXiv.2508.20717%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.48550%5C%2FarXiv.2508.20717%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22preprint%22%2C%22title%22%3A%22Unified%20Multi-task%20Learning%20for%20Voice-Based%20Detection%20of%20Diverse%20Clinical%20Conditions%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ran%22%2C%22lastName%22%3A%22Piao%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yuan%22%2C%22lastName%22%3A%22Lu%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hareld%22%2C%22lastName%22%3A%22Kemps%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tong%22%2C%22lastName%22%3A%22Xia%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Aaqib%22%2C%22lastName%22%3A%22Saeed%22%7D%5D%2C%22abstractNote%22%3A%22Voice-based%20health%20assessment%20offers%20unprecedented%20opportunities%20for%20scalable%2C%20non-invasive%20disease%20screening%2C%20yet%20existing%20approaches%20typically%20focus%20on%20single%20conditions%20and%20fail%20to%20leverage%20the%20rich%2C%20multi-faceted%20information%20embedded%20in%20speech.%20We%20present%20MARVEL%20%28Multi-task%20Acoustic%20Representations%20for%20Voice-based%20Health%20Analysis%29%2C%20a%20privacy-conscious%20multitask%20learning%20framework%20that%20simultaneously%20detects%20nine%20distinct%20neurological%2C%20respiratory%2C%20and%20voice%20disorders%20using%20only%20derived%20acoustic%20features%2C%20eliminating%20the%20need%20for%20raw%20audio%20transmission.%20Our%20dual-branch%20architecture%20employs%20specialized%20encoders%20with%20task-specific%20heads%20sharing%20a%20common%20acoustic%20backbone%2C%20enabling%20effective%20cross-condition%20knowledge%20transfer.%20Evaluated%20on%20the%20large-scale%20Bridge2AI-Voice%20v2.0%20dataset%2C%20MARVEL%20achieves%20an%20overall%20AUROC%20of%200.78%2C%20with%20exceptional%20performance%20on%20neurological%20disorders%20%28AUROC%20%3D%200.89%29%2C%20particularly%20for%20Alzheimer%26%23039%3Bs%20disease%5C%2Fmild%20cognitive%20impairment%20%28AUROC%20%3D%200.97%29.%20Our%20framework%20consistently%20outperforms%20single-modal%20baselines%20by%205-19%25%20and%20surpasses%20state-of-the-art%20self-supervised%20models%20on%207%20of%209%20tasks%2C%20while%20correlation%20analysis%20reveals%20that%20the%20learned%20representations%20exhibit%20meaningful%20similarities%20with%20established%20acoustic%20features%2C%20indicating%20that%20the%20model%26%23039%3Bs%20internal%20representations%20are%20consistent%20with%20clinically%20recognized%20acoustic%20patterns.%20By%20demonstrating%20that%20a%20single%20unified%20model%20can%20effectively%20screen%20for%20diverse%20conditions%2C%20this%20work%20establishes%20a%20foundation%20for%20deployable%20voice-based%20diagnostics%20in%20resource-constrained%20and%20remote%20healthcare%20settings.%22%2C%22genre%22%3A%22%22%2C%22repository%22%3A%22arXiv%22%2C%22archiveID%22%3A%22arXiv%3A2508.20717%22%2C%22date%22%3A%222025-08-28%22%2C%22DOI%22%3A%2210.48550%5C%2FarXiv.2508.20717%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22http%3A%5C%2F%5C%2Farxiv.org%5C%2Fabs%5C%2F2508.20717%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222025-12-11T14%3A15%3A52Z%22%7D%7D%2C%7B%22key%22%3A%2243U9N6FH%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Nejat%20et%20al.%22%2C%22parsedDate%22%3A%222025-08-21%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BNejat%2C%20P.%2C%20Bachman%2C%20A.%20D.%2C%20Stubbs%2C%20V.%20M.%2C%20Duffy%2C%20J.%20R.%2C%20Stricker%2C%20J.%20L.%2C%20Herasevich%2C%20V.%2C%20Jones%2C%20D.%20T.%2C%20Utianski%2C%20R.%20L.%2C%20%26amp%3B%20Botha%2C%20H.%20%282025%29.%20Who%20Makes%20It%20Through%20the%20Funnel%3F%20Sociodemographic%20Drivers%20of%20Recruitment%20Completion%20into%20an%20AI-Ready%20Digital%20Speech%20Bank.%20%26lt%3Bi%26gt%3BmedRxiv%26lt%3B%5C%2Fi%26gt%3B%2C%202025.08.18.25333909.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1101%5C%2F2025.08.18.25333909%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1101%5C%2F2025.08.18.25333909%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Who%20Makes%20It%20Through%20the%20Funnel%3F%20Sociodemographic%20Drivers%20of%20Recruitment%20Completion%20into%20an%20AI-Ready%20Digital%20Speech%20Bank%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Peyman%22%2C%22lastName%22%3A%22Nejat%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ashley%20D.%22%2C%22lastName%22%3A%22Bachman%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Vicki%20M.%22%2C%22lastName%22%3A%22Stubbs%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Joseph%20R.%22%2C%22lastName%22%3A%22Duffy%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22John%20L.%22%2C%22lastName%22%3A%22Stricker%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Vitaly%22%2C%22lastName%22%3A%22Herasevich%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%20T.%22%2C%22lastName%22%3A%22Jones%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rene%20L.%22%2C%22lastName%22%3A%22Utianski%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hugo%22%2C%22lastName%22%3A%22Botha%22%7D%5D%2C%22abstractNote%22%3A%22Background%3A%5CnDigital%20recruitment%20methods%20offer%20promising%20opportunities%20to%20address%20persistent%20challenges%20in%20clinical%20research%20participation%2C%20particularly%20in%20specialized%20fields%20like%20neurology.%20However%2C%20the%20impact%20of%20digital%20approaches%20across%20different%20socioeconomic%20and%20demographic%20groups%20remains%20inadequately%20understood.%20This%20study%20analyzed%20participant%20recruitment%20pathways%20in%20a%20digital%20neurology%20research%20study%20to%20identify%20sociodemographic%20factors%20associated%20with%20participation%20outcomes.%5Cn%5CnMethods%3A%5CnWe%20conducted%20a%20longitudinal%20analysis%20of%205%2C846%20patients%20invited%20to%20participate%20in%20a%20remote%20speech%20capture%20study%20for%20neurological%20disease%20research%20between%20March%20and%20July%202024.%20Using%20data%20from%20Qualtrics%2C%20PTrax%2C%20and%20our%20recording%20platform%2C%20we%20tracked%20participant%20progression%20through%20multiple%20recruitment%20checkpoints.%20Socioeconomic%20status%20was%20assessed%20using%20the%20Housing-based%20Socioeconomic%20Status%20%28HOUSES%29%20index%20and%20Area%20Deprivation%20Index%20%28ADI%29.%20We%20examined%20associations%20between%20participation%20pathways%20and%20demographic%20factors%20including%20age%2C%20sex%2C%20geographic%20location%2C%20and%20socioeconomic%20indices%20using%20Kruskal-Wallis%20and%20Wilcoxon%20rank-sum%20tests.%5Cn%5CnResults%3A%5CnOnly%20415%20participants%20%287.1%25%29%20completed%20all%20study%20requirements.%20Participants%20from%20neighborhoods%20with%20higher%20socioeconomic%20disadvantage%20%28higher%20ADI%20national%20ranks%29%20were%20significantly%20less%20likely%20to%20express%20interest%20in%20initial%20invitations%20%28median%20ADI%2045.0%20vs.%2042.0%20for%20responders%2C%20p%26lt%3B0.001%29.%20Urban%20participants%20completed%20enrollment%20faster%20than%20those%20from%20rural%20areas%20or%20urban%20clusters%20%28median%2032.0%20days%20vs.%2041.0%20and%2040.0%20days%2C%20p%3D0.011%29.%20Contrary%20to%20expectations%2C%20younger%20participants%20were%20more%20likely%20to%20drop%20out%20at%20multiple%20recruitment%20stages%2C%20with%20the%20median%20age%20increasing%20from%2063%20years%20in%20the%20invited%20cohort%20to%2066.3%20years%20among%20completers.%20Female%20participants%20required%20more%20time%20to%20complete%20enrollment%20compared%20to%20males%20%28median%2038.5%20days%20vs.%2032.0%20days%2C%20p%3D0.010%29.%20While%20neighborhood-level%20socioeconomic%20status%20significantly%20influenced%20participation%2C%20individual%20housing%20circumstances%20showed%20no%20significant%20association%20across%20recruitment%20stages.%5Cn%5CnConclusions%3A%5CnDigital%20recruitment%20methods%20in%20neurological%20research%20do%20not%20automatically%20overcome%20traditional%20barriers%20to%20participation%20and%20may%20introduce%20new%20disparities%20related%20to%20the%20digital%20divide.%20The%20significant%20associations%20between%20participation%20outcomes%20and%20sociodemographic%20factors%5Cu2014particularly%20neighborhood%20socioeconomic%20status%2C%20geographic%20location%2C%20age%2C%20and%20sex%5Cu2014highlight%20the%20need%20for%20targeted%20recruitment%20strategies.%20Researchers%20should%20implement%20multi-channel%20approaches%2C%20design%20age-specific%20engagement%20strategies%2C%20address%20geographic%20disparities%2C%20and%20consider%20socioeconomic%20factors%20to%20enhance%20the%20inclusivity%20and%20effectiveness%20of%20digital%20recruitment%20in%20neurological%20research.%22%2C%22date%22%3A%222025-8-21%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1101%5C%2F2025.08.18.25333909%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fpmc.ncbi.nlm.nih.gov%5C%2Farticles%5C%2FPMC12393637%5C%2F%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222025-12-11T14%3A19%3A58Z%22%7D%7D%2C%7B%22key%22%3A%223KRL8PUJ%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Jenkins%20et%20al.%22%2C%22parsedDate%22%3A%222025-08-12%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BJenkins%2C%20P.%2C%20Harrison%2C%20R.%2C%20Bedrick%2C%20S.%2C%20Karstens%2C%20L.%2C%20Bridge2AI-Voice%20Consortium%2C%20Hersh%2C%20W.%2C%20Bensoussan%2C%20Y.%2C%20Elemento%2C%20O.%2C%20Rameau%2C%20A.%2C%20Sigaras%2C%20A.%2C%20Ghosh%2C%20S.%2C%20Powell%2C%20M.%2C%20Ravitsky%2C%20V.%2C%20Belisle-Pipon%2C%20J.%20C.%2C%20Dorr%2C%20D.%2C%20Payne%2C%20P.%2C%20Johnson%2C%20A.%2C%20Bahr%2C%20R.%2C%20Bolser%2C%20D.%2C%20%26%23x2026%3B%20Goldenberg%2C%20A.%20%282025%29.%20Voice%20as%20a%20biomarker%3A%20exploratory%20analysis%20for%20benign%20and%20malignant%20vocal%20fold%20lesions.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Digital%20Health%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B7%26lt%3B%5C%2Fi%26gt%3B.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2025.1609811%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2025.1609811%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Voice%20as%20a%20biomarker%3A%20exploratory%20analysis%20for%20benign%20and%20malignant%20vocal%20fold%20lesions%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Phillip%22%2C%22lastName%22%3A%22Jenkins%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rylan%22%2C%22lastName%22%3A%22Harrison%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Bedrick%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lisa%22%2C%22lastName%22%3A%22Karstens%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22%22%2C%22lastName%22%3A%22Bridge2AI-Voice%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22William%22%2C%22lastName%22%3A%22Hersh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Olivier%22%2C%22lastName%22%3A%22Elemento%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anais%22%2C%22lastName%22%3A%22Rameau%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexandros%22%2C%22lastName%22%3A%22Sigaras%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Satrajit%22%2C%22lastName%22%3A%22Ghosh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maria%22%2C%22lastName%22%3A%22Powell%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Vardit%22%2C%22lastName%22%3A%22Ravitsky%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean%20Christophe%22%2C%22lastName%22%3A%22Belisle-Pipon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Dorr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Phillip%22%2C%22lastName%22%3A%22Payne%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alistair%22%2C%22lastName%22%3A%22Johnson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ruth%22%2C%22lastName%22%3A%22Bahr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Donald%22%2C%22lastName%22%3A%22Bolser%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Frank%22%2C%22lastName%22%3A%22Rudzicz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jordan%22%2C%22lastName%22%3A%22Lerner-Ellis%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Kathy%22%2C%22lastName%22%3A%22Jenkins%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shaheen%22%2C%22lastName%22%3A%22Awan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Micah%22%2C%22lastName%22%3A%22Boyer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22William%22%2C%22lastName%22%3A%22Hersh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andrea%22%2C%22lastName%22%3A%22Krussel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Bedrick%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Toufeeq%20Ahmed%22%2C%22lastName%22%3A%22Syed%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jamie%22%2C%22lastName%22%3A%22Toghranegar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22James%22%2C%22lastName%22%3A%22Anibal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Duncan%22%2C%22lastName%22%3A%22Sutherland%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Enrique%22%2C%22lastName%22%3A%22Diaz-Ocampo%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Elizabeth%22%2C%22lastName%22%3A%22Silberhoz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22John%22%2C%22lastName%22%3A%22Costello%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexander%22%2C%22lastName%22%3A%22Gelbard%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Kimberly%22%2C%22lastName%22%3A%22Vinson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tempestt%22%2C%22lastName%22%3A%22Neal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lochana%22%2C%22lastName%22%3A%22Jayachandran%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Evan%22%2C%22lastName%22%3A%22Ng%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Selina%22%2C%22lastName%22%3A%22Casalino%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yassmeen%22%2C%22lastName%22%3A%22Abdel-Aty%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Karim%22%2C%22lastName%22%3A%22Hanna%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Theresa%22%2C%22lastName%22%3A%22Zesiewicz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Elijah%22%2C%22lastName%22%3A%22Moothedan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Emily%22%2C%22lastName%22%3A%22Evangelista%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Samantha%20Salvi%22%2C%22lastName%22%3A%22Cruz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Robin%22%2C%22lastName%22%3A%22Zhao%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Mohamed%22%2C%22lastName%22%3A%22Ebraheem%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Karlee%22%2C%22lastName%22%3A%22Newberry%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Iris%20De%22%2C%22lastName%22%3A%22Santiago%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ellie%22%2C%22lastName%22%3A%22Eiseman%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22J.%20M.%22%2C%22lastName%22%3A%22Rahman%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stacy%22%2C%22lastName%22%3A%22Jo%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anna%22%2C%22lastName%22%3A%22Goldenberg%22%7D%5D%2C%22abstractNote%22%3A%22Benign%20and%20malignant%20vocal%20fold%20lesions%20can%20alter%20voice%20quality%20and%20lead%20to%20significant%20morbidity%20or%2C%20in%20the%20case%20of%20malignancy%2C%20mortality.%20Early%2C%20noninvasive%20identification%20of%20these%20lesions%20using%20voice%20as%20a%20biomarker%20may%20improve%20diagnostic%20access%20and%20outcomes.%20In%20this%20study%2C%20we%20analyzed%20data%20from%20the%20initial%20release%20of%20the%20Bridge2AI-Voice%20dataset%20to%20evaluate%20which%20acoustic%20features%20best%20distinguish%20laryngeal%20cancer%20and%20benign%20vocal%20fold%20lesions%20from%20other%20vocal%20pathologies%20and%20healthy%20voice%20function.%20Seven%20diagnostic%20cohorts%20were%20grouped%20into%20two%20analyses%3A%20the%20first%20included%20participants%20with%20laryngeal%20cancer%2C%20benign%20lesions%2C%20or%20no%20voice%20disorder%3B%20the%20second%20included%20those%20with%20laryngeal%20cancer%20or%20benign%20lesions%20without%20other%20voice%20disorders%2C%20as%20well%20as%20individuals%20with%20spasmodic%20dysphonia%20or%20vocal%20fold%20paralysis.%20Acoustic%20features%20including%20fundamental%20frequency%2C%20jitter%2C%20shimmer%2C%20and%20harmonic-to-noise%20ratio%20%28HNR%29%20were%20extracted%20from%20standardized%20speech%20recordings%20and%20compared%20using%20nonparametric%20statistical%20methods.%20Among%20the%20overall%20sample%2C%20significant%20differences%20were%20identified%20in%20HNR%20and%20fundamental%20frequency%20between%20benign%20lesions%20and%20both%20healthy%20controls%20and%20laryngeal%20cancer.%20In%20cisgender%20men%2C%20these%20distinctions%20were%20also%20observed%2C%20particularly%20in%20HNR%20and%20its%20variability.%20No%20statistically%20significant%20differences%20were%20observed%20among%20cisgender%20women%2C%20likely%20due%20to%20the%20limited%20sample%20size.%20These%20findings%20suggest%20that%20HNR%2C%20particularly%20its%20variability%2C%20may%20hold%20promise%20as%20a%20voice-based%20marker%20for%20early%20detection%20and%20monitoring%20of%20vocal%20fold%20lesions.%20Further%20research%20with%20larger%2C%20more%20diverse%20populations%20is%20needed%20to%20refine%20these%20features%20and%20validate%20their%20clinical%20utility.%22%2C%22date%22%3A%222025-08-12%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffdgth.2025.1609811%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Fjournals%5C%2Fdigital-health%5C%2Farticles%5C%2F10.3389%5C%2Ffdgth.2025.1609811%5C%2Ffull%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-253X%22%2C%22language%22%3A%22English%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222025-08-26T12%3A47%3A05Z%22%7D%7D%2C%7B%22key%22%3A%22VBLPABDB%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Awan%20et%20al.%22%2C%22parsedDate%22%3A%222025-07-09%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BAwan%2C%20S.%20N.%2C%20Bensoussan%2C%20Y.%2C%20Watts%2C%20S.%2C%20Boyer%2C%20M.%2C%20Budinsky%2C%20R.%2C%20%26amp%3B%20Bahr%2C%20R.%20H.%20%282025%29.%20Influence%20of%20recording%20instrumentation%20on%20measurements%20of%20voice%20in%20sentence%20contexts%3A%20use%20of%20smartphones%20and%20tablets.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Digital%20Health%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B7%26lt%3B%5C%2Fi%26gt%3B.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2025.1610772%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2025.1610772%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Influence%20of%20recording%20instrumentation%20on%20measurements%20of%20voice%20in%20sentence%20contexts%3A%20use%20of%20smartphones%20and%20tablets%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shaheen%20N.%22%2C%22lastName%22%3A%22Awan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stephanie%22%2C%22lastName%22%3A%22Watts%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Micah%22%2C%22lastName%22%3A%22Boyer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Robert%22%2C%22lastName%22%3A%22Budinsky%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ruth%20H.%22%2C%22lastName%22%3A%22Bahr%22%7D%5D%2C%22abstractNote%22%3A%22IntroductionThe%20Bridge2AI-Voice.%20Consortium%20is%20developing%20affordable%20and%20accessible%20voice%20data%20to%20assist%20in%20the%20identification%20of%20vocal%20biomarkers%20of%20disease%20in%20adults%20and%20children.%20Initial%20experiments%20were%20designed%20to%20establish%20voice%20recording%20procedures%20to%20be%20used%20in%20research%20labs%20and%20clinical%20settings%2C%20as%20well%20as%20in%20quiet%20environments%20outside%20of%20the%20clinic.%20The%20focus%20has%20been%20on%20isolated%20vowel%20productions%2C%20which%20provide%20a%20vocal%20signal%20that%20is%20representative%20of%20the%20biomechanics%20of%20the%20larynx%20within%20a%20static%20vocal%20tract.%20The%20current%20experiment%20considers%20the%20impact%20of%20sentence%20productions%20on%20the%20measurement%20of%20several%20acoustic%20parameters.MethodsVoice%20recordings%20from%2024%20individuals%20representing%20a%20wide%20range%20of%20typical%20and%20disordered%20voices%20were%20analyzed.%20Two%20CAPE-V%20sentences%20were%20recorded%20via%20a%20head-and-torso%20model%20using%20%281%29%20a%20research%20quality%2C%20clinical%20standard%20microphone%5C%2Fpreamplifier%5C%2Faudio%20interface%20and%20%282%29%20smartphones%20and%20tablets%20using%20their%20internal%20microphones%20and%20an%20attached%20external%20headset%20microphone.%20Mouth-to-microphone%20distances%20and%20environmental%20noise%20levels%20were%20controlled.%20Measures%20of%20fundamental%20frequency%20%28F0%29%20and%20spectral%20and%20cepstral%20measures%20of%20voice%20quality%20valid%20for%20use%20in%20sentence%20contexts%20were%20analyzed%20across%20recording%20conditions.ResultsCepstral%20peak%20prominence%20%28CPP%29%20values%20were%20sensitive%20to%20microphone%20type%2C%20noise%2C%20and%20sentence%20type%20conditions.%20Nevertheless%2C%20strong%20linear%20relationships%20were%20observed%20across%20recording%20methods%20compared%20to%20the%20clinical%20standard.%20Measures%20of%20F0%20obtained%20using%20autocorrelation%20correlated%20strongly%20across%20recording%20methods%2C%20whereas%20F0%20measures%20obtained%20from%20the%20CPP%20%28CPP%20F0%29%20were%20highly%20variable%20and%20poorly%20correlated%20across%20recording%20methods%20and%20noise%20conditions.%20The%20L%5C%2FH%20ratio%20%28a%20measure%20of%20spectral%20tilt%29%20was%20significantly%20affected%20by%20recording%20condition%20but%20not%20background%20noise%2C%20and%20measures%20of%20L%5C%2FH%20ratio%20were%20also%20observed%20to%20correlate%20strongly%20across%20recording%20methods%20and%20noise%20conditions.DiscussionCurrent%20findings%20revealed%20that%20different%20recording%20methods%20can%20produce%20significantly%20different%20acoustic%20measures%20of%20voice%20with%20sentence-level%20materials.%20Since%20microphone%20characteristics%20%28e.g.%2C%20frequency%20response%3B%20use%20of%20noise%20cancellation%29%2C%20mouth-to-microphone%20distances%2C%20and%20background%20noise%20conditions%20can%20have%20significant%20effects%20on%20spectral%20and%20cepstral%20assessment%20of%20voice%2C%20it%20is%20essential%20that%20recording%20methods%20and%20conditions%20are%20explicitly%20described%20when%20designing%20voice%20data%20collection%20projects%20and%20comparing%20datasets%20as%20it%20may%20have%20an%20impact%20on%20voice%20analysis.%20Future%20investigations%20should%20evaluate%20consistency%20of%20results%20among%20multiple%20examples%20of%20the%20same%20device.%22%2C%22date%22%3A%222025-07-09%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffdgth.2025.1610772%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Fjournals%5C%2Fdigital-health%5C%2Farticles%5C%2F10.3389%5C%2Ffdgth.2025.1610772%5C%2Ffull%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-253X%22%2C%22language%22%3A%22English%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222025-09-10T21%3A25%3A04Z%22%7D%7D%2C%7B%22key%22%3A%22A3MT9HEY%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Kalia%20et%20al.%22%2C%22parsedDate%22%3A%222025-06-27%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BKalia%2C%20A.%2C%20Boyer%2C%20M.%2C%20Fagherazzi%2C%20G.%2C%20B%26%23xE9%3Blisle-Pipon%2C%20J.-C.%2C%20%26amp%3B%20Bensoussan%2C%20Y.%20%282025%29.%20Master%20protocols%20in%20vocal%20biomarker%20development%20to%20reduce%20variability%20and%20advance%20clinical%20precision%3A%20a%20narrative%20review.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Digital%20Health%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B7%26lt%3B%5C%2Fi%26gt%3B.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2025.1619183%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2025.1619183%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Master%20protocols%20in%20vocal%20biomarker%20development%20to%20reduce%20variability%20and%20advance%20clinical%20precision%3A%20a%20narrative%20review%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ayush%22%2C%22lastName%22%3A%22Kalia%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Micah%22%2C%22lastName%22%3A%22Boyer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Guy%22%2C%22lastName%22%3A%22Fagherazzi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Christophe%22%2C%22lastName%22%3A%22B%5Cu00e9lisle-Pipon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%5D%2C%22abstractNote%22%3A%22IntroductionVocal%20biomarkers%2C%20defined%20as%20acoustic%20or%20linguistic%20features%20extracted%20from%20voice%20samples%2C%20are%20an%20emerging%20innovation%20in%20medical%20diagnostics.%20Utilizing%20artificial%20intelligence%2C%20machine%20learning%2C%20or%20traditional%20acoustic%20analysis%2C%20vocal%20biomarkers%20have%20shown%20promise%20in%20detecting%20and%20monitoring%20conditions%20such%20as%20respiratory%20disorders%20and%20cognitive%20impairments.%20Despite%20their%20potential%2C%20the%20lack%20of%20standardized%20protocols%20for%20data%20collection%20and%20analysis%20has%20limited%20their%20clinical%20applicability.ObjectivesThis%20review%20assesses%20the%20current%20state%20of%20research%20on%20developing%20a%20master%20protocol%20for%20vocal%20biomarkers%2C%20identifying%20key%20aspects%20essential%20for%20reducing%20variability%20across%20studies.%20It%20also%20explores%20insights%20from%20digital%20biomarker%20research%20to%20inform%20the%20creation%20of%20a%20standardized%20framework%20for%20vocal%20biomarker%20development.MethodsA%20narrative%20review%20was%20conducted%20by%20searching%20PubMed%20for%20literature%20on%20vocal%20and%20digital%20biomarker%20development.%20Articles%20were%20evaluated%20based%20on%20their%20proposed%20frameworks%20and%20recommendations%20for%20addressing%20methodological%20inconsistencies.ResultsTwenty-one%20relevant%20articles%20were%20identified%2C%20including%2012%20focused%20on%20vocal%20biomarkers%20and%209%20addressing%20broader%20digital%20biomarkers.%20Vocal%20biomarker%20literature%20emphasized%20the%20lack%20of%20existing%20master%20protocols%20and%20the%20need%20for%20standardization.%20In%20contrast%2C%20digital%20biomarker%20research%20from%20organizations%20like%20the%20Digital%20Medicine%20Society%20offered%20structured%20frameworks%20applicable%20to%20voice%20research.ConclusionThere%20is%20currently%20no%20established%20master%20protocol%20for%20vocal%20biomarker%20development.%20This%20review%20highlights%20foundational%20elements%20necessary%20for%20future%20standardization%20efforts%20to%20support%20the%20clinical%20integration%20of%20vocal%20biomarkers%20in%20healthcare.%22%2C%22date%22%3A%222025-06-27%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffdgth.2025.1619183%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Fjournals%5C%2Fdigital-health%5C%2Farticles%5C%2F10.3389%5C%2Ffdgth.2025.1619183%5C%2Ffull%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-253X%22%2C%22language%22%3A%22English%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222025-12-11T14%3A19%3A01Z%22%7D%7D%2C%7B%22key%22%3A%22Q4BHJXWU%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Blatter%20et%20al.%22%2C%22parsedDate%22%3A%222025-05-29%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BBlatter%2C%20A.%2C%20Gallois%2C%20H.%2C%20Evangelista%2C%20E.%2C%20Bensoussan%2C%20Y.%2C%20Bridge2AI-Voice%20Consortium%2C%20%26amp%3B%20B%26%23xE9%3Blisle-Pipon%2C%20J.-C.%20%282025%29.%20%26%23x201C%3BVoice%20is%20the%20New%20Blood%26%23x201D%3B%3A%20a%20discourse%20analysis%20of%20voice%20AI%20health-tech%20start-up%20websites.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Digital%20Health%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B7%26lt%3B%5C%2Fi%26gt%3B%2C%201568159.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2025.1568159%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2025.1568159%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22%5Cu201cVoice%20is%20the%20New%20Blood%5Cu201d%3A%20a%20discourse%20analysis%20of%20voice%20AI%20health-tech%20start-up%20websites%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alden%22%2C%22lastName%22%3A%22Blatter%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hortense%22%2C%22lastName%22%3A%22Gallois%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Emily%22%2C%22lastName%22%3A%22Evangelista%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22Bridge2AI-Voice%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Christophe%22%2C%22lastName%22%3A%22B%5Cu00e9lisle-Pipon%22%7D%5D%2C%22abstractNote%22%3A%22Introduction%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Voice%20as%20a%20biomarker%20has%20emerged%20as%20a%20transformative%20field%20in%20health%20technology%2C%20providing%20non-invasive%2C%20accessible%2C%20and%20cost-effective%20methods%20for%20detecting%2C%20diagnosing%2C%20and%20monitoring%20various%20conditions.%20Start-ups%20are%20at%20the%20forefront%20of%20this%20innovative%20field%2C%20developing%20and%20marketing%20clinical%20voice%20AI%20solutions%20to%20a%20range%20of%20healthcare%20actors%20and%20shaping%20the%20field%26%23039%3Bs%20early%20development.%20However%2C%20there%20is%20limited%20understanding%20of%20how%20start-ups%20in%20this%20field%20frame%20their%20innovations%2C%20and%20address%5Cu2014or%20overlook%5Cu2014critical%20socio-ethical%2C%20technical%2C%20and%20regulatory%20challenges%20in%20the%20rapidly%20evolving%20field%20of%20digital%20health.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Methods%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20This%20study%20uses%20discourse%20analysis%20to%20examine%20the%20language%20on%20the%20public%20websites%20of%2025%20voice%20AI%20health-tech%20start-ups.%20Grounded%20in%20constitutive%20discourse%20analysis%2C%20which%20asserts%20that%20discourse%20both%20reflects%20and%20shapes%20realities%2C%20the%20study%20identifies%20patterns%20in%20how%20these%20companies%20describe%20their%20identities%2C%20technologies%2C%20and%20datasets.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Results%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20The%20analysis%20shows%20start-ups%20consistently%20highlight%20the%20efficacy%2C%20reliability%2C%20and%20safety%20of%20their%20technologies%2C%20positioning%20them%20as%20transformative%20healthcare%20solutions.%20However%2C%20descriptions%20of%20voice%20datasets%20used%20to%20train%20algorithms%20vary%20widely%20and%20are%20often%20absent%2C%20reflecting%20broader%20gaps%20in%20acoustic%20and%20ethical%20standards%20for%20voice%20data%20collection%20and%20insufficient%20incentives%20for%20start-ups%20to%20disclose%20key%20data%20details.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Discussion%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Start-ups%20play%20a%20crucial%20role%20in%20the%20research%2C%20development%2C%20and%20marketization%20of%20voice%20AI%20health-tech%2C%20prefacing%20the%20integration%20of%20this%20new%20technology%20into%20healthcare%20systems.%20By%20publicizing%20discourse%20around%20voice%20AI%20technologies%20at%20this%20early%20stage%2C%20start-ups%20are%20shaping%20public%20perceptions%2C%20setting%20expectations%20for%20end-users%2C%20and%20ultimately%20influencing%20the%20implementation%20of%20voice%20AI%20technologies%20in%20healthcare.%20Their%20discourse%20seems%20to%20strategically%20present%20voice%20AI%20health-tech%20as%20legitimate%20by%20using%20promissory%20language%20typical%20in%20the%20digital%20health%20field%20and%20showcase%20the%20distinctiveness%20from%20competitors.%20This%20analysis%20highlights%20how%20this%20double%20impetus%20often%20drives%20narratives%20that%20prioritize%20innovation%20over%20transparency.%20We%20conclude%20that%20the%20lack%20of%20incentive%20to%20share%20key%20information%20about%20datasets%20is%20due%20to%20contextual%20factors%20that%20start-ups%20cannot%20control%2C%20mainly%20the%20absence%20of%20clear%20standards%20and%20regulatory%20guidelines%20for%20voice%20data%20collection.%20Addressing%20these%20complexities%20is%20essential%20to%20building%20trust%20and%20ensuring%20responsible%20integration%20of%20voice%20AI%20into%20healthcare%20systems.%22%2C%22date%22%3A%222025-5-29%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffdgth.2025.1568159%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Farticles%5C%2F10.3389%5C%2Ffdgth.2025.1568159%5C%2Ffull%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-253X%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-07-20T18%3A01%3A47Z%22%7D%7D%2C%7B%22key%22%3A%22VV54W8BE%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Anibal%20et%20al.%22%2C%22parsedDate%22%3A%222025-05-02%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BAnibal%2C%20J.%2C%20Doctor%2C%20R.%2C%20Boyer%2C%20M.%2C%20Newberry%2C%20K.%2C%20De%20Santiago%2C%20I.%2C%20Awan%2C%20S.%2C%20Abdel-Aty%2C%20Y.%2C%20Dion%2C%20G.%2C%20Daoud%2C%20V.%2C%20Huth%2C%20H.%2C%20Watts%2C%20S.%2C%20Wood%2C%20B.%20J.%2C%20Clifton%2C%20D.%2C%20Gelbard%2C%20A.%2C%20Powell%2C%20M.%2C%20Toghranegar%2C%20J.%2C%20%26amp%3B%20Bensoussan%2C%20Y.%20%282025%29.%20Transformers%20for%20rapid%20detection%20of%20airway%20stenosis%20and%20stridor.%20%26lt%3Bi%26gt%3BScientific%20Reports%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B15%26lt%3B%5C%2Fi%26gt%3B%281%29%2C%2015394.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41598-025-99369-y%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41598-025-99369-y%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Transformers%20for%20rapid%20detection%20of%20airway%20stenosis%20and%20stridor%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22James%22%2C%22lastName%22%3A%22Anibal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rebecca%22%2C%22lastName%22%3A%22Doctor%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Micah%22%2C%22lastName%22%3A%22Boyer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Karlee%22%2C%22lastName%22%3A%22Newberry%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Iris%22%2C%22lastName%22%3A%22De%20Santiago%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shaheen%22%2C%22lastName%22%3A%22Awan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yassmeen%22%2C%22lastName%22%3A%22Abdel-Aty%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Gregory%22%2C%22lastName%22%3A%22Dion%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Veronica%22%2C%22lastName%22%3A%22Daoud%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hannah%22%2C%22lastName%22%3A%22Huth%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stephanie%22%2C%22lastName%22%3A%22Watts%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Bradford%20J.%22%2C%22lastName%22%3A%22Wood%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Clifton%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexander%22%2C%22lastName%22%3A%22Gelbard%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maria%22%2C%22lastName%22%3A%22Powell%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jamie%22%2C%22lastName%22%3A%22Toghranegar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%5D%2C%22abstractNote%22%3A%22Upper%20airway%20stenosis%20is%20a%20potentially%20life-threatening%20condition%20involving%20the%20narrowing%20of%20the%20airway.%20In%20more%20severe%20cases%2C%20airway%20stenosis%20may%20be%20accompanied%20by%20stridor%2C%20a%20type%20of%20disordered%20breathing%20caused%20by%20turbulent%20airflow.%20Patients%20with%20airway%20stenosis%20have%20a%20higher%20risk%20of%20airway%20failure%20and%20additional%20precautions%20must%20be%20taken%20before%20medical%20interventions%20like%20intubation.%20However%2C%20stenosis%20and%20stridor%20are%20often%20misdiagnosed%20as%20other%20respiratory%20conditions%20like%20asthma%5C%2Fwheezing%2C%20worsening%20outcomes.%20This%20report%20presents%20a%20unified%20dataset%20containing%20recorded%20breathing%20tasks%20from%20patients%20with%20stridor%20and%20airway%20stenosis.%20Customized%20transformer-based%20models%20were%20also%20trained%20to%20perform%20stenosis%20and%20stridor%20detection%20tasks%20using%20low-cost%20data%20from%20multiple%20acoustic%20prompts%20recorded%20on%20common%20devices.%20These%20methods%20achieved%20AUC%20scores%20of%200.875%20for%20stenosis%20detection%20and%200.864%20for%20stridor%20detection%2C%20demonstrating%20the%20potential%20to%20add%20value%20as%20screening%20tools%20in%20real-world%20clinical%20workflows%2C%20particularly%20in%20high-volume%20settings%20like%20emergency%20departments.%22%2C%22date%22%3A%222025-05-02%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1038%5C%2Fs41598-025-99369-y%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.nature.com%5C%2Farticles%5C%2Fs41598-025-99369-y%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222045-2322%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222025-08-26T13%3A32%3A01Z%22%7D%7D%2C%7B%22key%22%3A%224DCVBVY6%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Moothedan%20et%20al.%22%2C%22parsedDate%22%3A%222025-04-15%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BMoothedan%2C%20E.%2C%20Boyer%2C%20M.%2C%20Watts%2C%20S.%2C%20Abdel-Aty%2C%20Y.%2C%20Ghosh%2C%20S.%2C%20Rameau%2C%20A.%2C%20Sigaras%2C%20A.%2C%20Elemento%2C%20O.%2C%20Bridge2AI-Voice%20Consortium%2C%20%26amp%3B%20Bensoussan%2C%20Y.%20%282025%29.%20The%20Bridge2AI-voice%20application%3A%20initial%20feasibility%20study%20of%20voice%20data%20acquisition%20through%20mobile%20health.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Digital%20Health%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B7%26lt%3B%5C%2Fi%26gt%3B%2C%201514971.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2025.1514971%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2025.1514971%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22The%20Bridge2AI-voice%20application%3A%20initial%20feasibility%20study%20of%20voice%20data%20acquisition%20through%20mobile%20health%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Elijah%22%2C%22lastName%22%3A%22Moothedan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Micah%22%2C%22lastName%22%3A%22Boyer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stephanie%22%2C%22lastName%22%3A%22Watts%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yassmeen%22%2C%22lastName%22%3A%22Abdel-Aty%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Satrajit%22%2C%22lastName%22%3A%22Ghosh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ana%5Cu00efs%22%2C%22lastName%22%3A%22Rameau%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexandros%22%2C%22lastName%22%3A%22Sigaras%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Olivier%22%2C%22lastName%22%3A%22Elemento%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22Bridge2AI-Voice%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%5D%2C%22abstractNote%22%3A%22Introduction%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Bridge2AI-Voice%2C%20a%20collaborative%20multi-institutional%20consortium%2C%20aims%20to%20generate%20a%20large-scale%2C%20ethically%20sourced%20voice%2C%20speech%2C%20and%20cough%20database%20linked%20to%20health%20metadata%20in%20order%20to%20support%20AI-driven%20research.%20A%20novel%20smartphone%20application%2C%20the%20Bridge2AI-Voice%20app%2C%20was%20created%20to%20collect%20standardized%20recordings%20of%20acoustic%20tasks%2C%20validated%20patient%20questionnaires%2C%20and%20validated%20patient%20reported%20outcomes.%20Before%20broad%20data%20collection%2C%20a%20feasibility%20study%20was%20undertaken%20to%20assess%20the%20viability%20of%20the%20app%20in%20a%20clinical%20setting%20through%20task%20performance%20metrics%20and%20participant%20feedback.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Materials%20%26amp%3B%20methods%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Participants%20were%20recruited%20from%20a%20tertiary%20academic%20voice%20center.%20Participants%20were%20instructed%20to%20complete%20a%20series%20of%20tasks%20through%20the%20application%20on%20an%20iPad.%20The%20Plan-Do-Study-Act%20model%20for%20quality%20improvement%20was%20implemented.%20Data%20collected%20included%20demographics%20and%20task%20metrics%20including%20time%20of%20completion%2C%20successful%20task%5C%2Frecording%20completion%2C%20and%20need%20for%20assistance.%20Participant%20feedback%20was%20measured%20by%20a%20qualitative%20interview%20adapted%20from%20the%20Mobile%20App%20Rating%20Scale.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Results%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Forty-seven%20participants%20were%20enrolled%20%2861%25%20female%2C%2092%25%20reported%20primary%20language%20of%20English%2C%20mean%20age%20of%2058.3%20years%29.%20All%20owned%20smart%20devices%2C%20with%2049%25%20using%20mobile%20health%20apps.%20Overall%20task%20completion%20rate%20was%2068%25%2C%20with%20acoustic%20tasks%20successfully%20recorded%20in%2041%25%20of%20cases.%20Participants%20requested%20assistance%20in%2041%25%20of%20successfully%20completed%20tasks%2C%20with%20challenges%20mainly%20related%20to%20design%20and%20instruction%20understandability.%20Interview%20responses%20reflected%20favorable%20perception%20of%20voice-screening%20apps%20and%20their%20features.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Conclusion%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Findings%20suggest%20that%20the%20Bridge2AI-Voice%20application%20is%20a%20promising%20tool%20for%20voice%20data%20acquisition%20in%20a%20clinical%20setting.%20However%2C%20development%20of%20improved%20User%20Interface%5C%2FUser%20Experience%20and%20broader%2C%20diverse%20feasibility%20studies%20are%20needed%20for%20a%20usable%20tool.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20Level%20of%20evidence%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3A%203.%22%2C%22date%22%3A%222025-4-15%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffdgth.2025.1514971%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Farticles%5C%2F10.3389%5C%2Ffdgth.2025.1514971%5C%2Ffull%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-253X%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222026-07-16T21%3A15%3A38Z%22%7D%7D%2C%7B%22key%22%3A%225P3CXJRH%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22D%5Cu00edaz-Ocampo%20et%20al.%22%2C%22parsedDate%22%3A%222025-04-01%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BD%26%23xED%3Baz-Ocampo%2C%20E.%2C%20Mart%26%23xED%3Bnez-Tapia%2C%20A.%2C%20Magadan-Salazar%2C%20A.%2C%20Pinto%20El%26%23xED%3Bas%2C%20R.%2C%20Lopez%2C%20M.%2C%20%26amp%3B%20Bensoussan%2C%20Y.%20%282025%29.%20Gender%20Recognition%20of%20Teen%20and%20Adult%20Voices%20in%20Non-Tonal%20and%20Tonal%20Languages%20in%20Uncontrolled%20Environments.%20%26lt%3Bi%26gt%3BComputaci%26%23xF3%3Bn%20y%20Sistemas%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B29%26lt%3B%5C%2Fi%26gt%3B.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.13053%5C%2Fcys-29-1-4495%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.13053%5C%2Fcys-29-1-4495%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Gender%20Recognition%20of%20Teen%20and%20Adult%20Voices%20in%20Non-Tonal%20and%20Tonal%20Languages%20in%20Uncontrolled%20Environments%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Enrique%22%2C%22lastName%22%3A%22D%5Cu00edaz-Ocampo%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Areli%22%2C%22lastName%22%3A%22Mart%5Cu00ednez-Tapia%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andrea%22%2C%22lastName%22%3A%22Magadan-Salazar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ra%5Cu00fal%22%2C%22lastName%22%3A%22Pinto%20El%5Cu00edas%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maximo%22%2C%22lastName%22%3A%22Lopez%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222025-04-01%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.13053%5C%2Fcys-29-1-4495%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222025-08-26T13%3A18%3A11Z%22%7D%7D%2C%7B%22key%22%3A%22WV7QADPQ%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22B%5Cu00e9lisle-Pipon%20et%20al.%22%2C%22parsedDate%22%3A%222025-03-27%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BB%26%23xE9%3Blisle-Pipon%2C%20J.-C.%2C%20Anibal%2C%20J.%2C%20Bahr%2C%20R.%2C%20Bedrick%2C%20S.%2C%20Coleman%2C%20O.%2C%20Dorr%2C%20D.%2C%20Evans%2C%20B.%20J.%2C%20Fagherazzi%2C%20G.%2C%20Gelbard%2C%20A.%2C%20Ghosh%2C%20S.%2C%20Ho%2C%20A.%2C%20Jackson%2C%20C.%2C%20Joachim%2C%20D.%2C%20Kourtis%2C%20L.%2C%20Krussel%2C%20A.%2C%20Lahav%2C%20A.%2C%20Leuze%2C%20B.%2C%20MacDonald%2C%20B.%2C%20Miller%2C%20G.%2C%20%26%23x2026%3B%20Bensoussan%2C%20Y.%20%282025%29.%20Interactive%20Panel%20Summaries%20of%20the%202024%20Voice%20AI%20Symposium.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Digital%20Health%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B7%26lt%3B%5C%2Fi%26gt%3B%2C%201484521.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2025.1484521%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2025.1484521%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Interactive%20Panel%20Summaries%20of%20the%202024%20Voice%20AI%20Symposium%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Christophe%22%2C%22lastName%22%3A%22B%5Cu00e9lisle-Pipon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22James%22%2C%22lastName%22%3A%22Anibal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ruth%22%2C%22lastName%22%3A%22Bahr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Bedrick%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Oita%22%2C%22lastName%22%3A%22Coleman%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Dorr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Barbara%20J.%22%2C%22lastName%22%3A%22Evans%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Guy%22%2C%22lastName%22%3A%22Fagherazzi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexander%22%2C%22lastName%22%3A%22Gelbard%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Satrajit%22%2C%22lastName%22%3A%22Ghosh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anita%22%2C%22lastName%22%3A%22Ho%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christie%22%2C%22lastName%22%3A%22Jackson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Dale%22%2C%22lastName%22%3A%22Joachim%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lampros%22%2C%22lastName%22%3A%22Kourtis%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andrea%22%2C%22lastName%22%3A%22Krussel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Amir%22%2C%22lastName%22%3A%22Lahav%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Breanna%22%2C%22lastName%22%3A%22Leuze%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Bob%22%2C%22lastName%22%3A%22MacDonald%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Geralyn%22%2C%22lastName%22%3A%22Miller%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Vivek%22%2C%22lastName%22%3A%22Mohan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Matthew%22%2C%22lastName%22%3A%22Naunheim%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maria%22%2C%22lastName%22%3A%22Powell%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ana%5Cu00efs%22%2C%22lastName%22%3A%22Rameau%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sat%22%2C%22lastName%22%3A%22Ramphal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Vardit%22%2C%22lastName%22%3A%22Ravitsky%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Charlie%22%2C%22lastName%22%3A%22Reavis%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Samantha%22%2C%22lastName%22%3A%22Salvi%20Cruz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jamie%22%2C%22lastName%22%3A%22Toghranegar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Adam%22%2C%22lastName%22%3A%22Vogel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stephanie%22%2C%22lastName%22%3A%22Watts%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Joseph%22%2C%22lastName%22%3A%22Yracheta%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Robin%22%2C%22lastName%22%3A%22Zhao%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22The%20Bridge2AI-Voice%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%5D%2C%22abstractNote%22%3A%22The%202024%20Voice%20AI%20Symposium%20presented%20by%20the%20Bridge2AI-Voice%20Consortium%2C%20was%20a%202-day%20event%20which%20took%20place%20May%201st-May%202nd%20in%20Tampa%2C%20FL.%20The%20event%20included%20four%20interactive%20panel%20sessions%2C%20which%20are%20summarized%20here.%20All%20four%20interactive%20panels%20featured%20an%20innovative%20format%2C%20designed%20to%20maximize%20engagement%20and%20facilitate%20deep%20discussions.%20Each%20panel%20began%20with%20a%2045%5Cu2005min%20segment%20where%20moderators%20posed%20targeted%20questions%20to%20expert%20panelists%2C%20delving%20into%20complex%20topics%20within%20the%20field%20of%20voice%20AI.%20This%20was%20followed%20by%20a%2045%5Cu2005min%20%5Cu201cstakeholder%20forum%2C%5Cu201d%20during%20which%20audience%20members%20asked%20questions%20and%20engaged%20in%20live%20interactive%20polls.%20Interactive%20polls%20stimulated%20meaningful%20conversation%20between%20panelists%20and%20attendees%2C%20and%20brought%20to%20light%20diverse%20viewpoints.%20Workshops%20were%20audio%20recorded%20and%20transcripts%20were%20assembled%20with%20assistance%20from%20generative%20A.I%20tools%20including%20Whisper%20Version%207.13.1%20for%20audio%20transcription%20and%20ChatGPT%20version%204.0%20for%20content%20summation.%20Content%20was%20then%20reviewed%20and%20edited%20by%20authors.%22%2C%22date%22%3A%222025-3-27%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffdgth.2025.1484521%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Farticles%5C%2F10.3389%5C%2Ffdgth.2025.1484521%5C%2Ffull%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-253X%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-07-20T18%3A06%3A50Z%22%7D%7D%2C%7B%22key%22%3A%22DC2J2L5H%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Anibal%20et%20al.%22%2C%22parsedDate%22%3A%222025-01-28%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BAnibal%2C%20J.%2C%20Huth%2C%20H.%2C%20Li%2C%20M.%2C%20Hazen%2C%20L.%2C%20Daoud%2C%20V.%2C%20Ebedes%2C%20D.%2C%20Lam%2C%20Y.%20M.%2C%20Nguyen%2C%20H.%2C%20Hong%2C%20P.%20V.%2C%20Kleinman%2C%20M.%2C%20Ost%2C%20S.%2C%20Jackson%2C%20C.%2C%20Sprabery%2C%20L.%2C%20Elangovan%2C%20C.%2C%20Krishnaiah%2C%20B.%2C%20Akst%2C%20L.%2C%20Lina%2C%20I.%2C%20Elyazar%2C%20I.%2C%20Ekawati%2C%20L.%2C%20%26%23x2026%3B%20Wood%2C%20B.%20%282025%29.%20Voice%20EHR%3A%20introducing%20multimodal%20audio%20data%20for%20health.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Digital%20Health%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B6%26lt%3B%5C%2Fi%26gt%3B%2C%201448351.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2024.1448351%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2024.1448351%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Voice%20EHR%3A%20introducing%20multimodal%20audio%20data%20for%20health%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22James%22%2C%22lastName%22%3A%22Anibal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hannah%22%2C%22lastName%22%3A%22Huth%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ming%22%2C%22lastName%22%3A%22Li%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lindsey%22%2C%22lastName%22%3A%22Hazen%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Veronica%22%2C%22lastName%22%3A%22Daoud%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Dominique%22%2C%22lastName%22%3A%22Ebedes%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yen%20Minh%22%2C%22lastName%22%3A%22Lam%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hang%22%2C%22lastName%22%3A%22Nguyen%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Phuc%20Vo%22%2C%22lastName%22%3A%22Hong%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Michael%22%2C%22lastName%22%3A%22Kleinman%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shelley%22%2C%22lastName%22%3A%22Ost%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christopher%22%2C%22lastName%22%3A%22Jackson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Laura%22%2C%22lastName%22%3A%22Sprabery%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Cheran%22%2C%22lastName%22%3A%22Elangovan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Balaji%22%2C%22lastName%22%3A%22Krishnaiah%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lee%22%2C%22lastName%22%3A%22Akst%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ioan%22%2C%22lastName%22%3A%22Lina%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Iqbal%22%2C%22lastName%22%3A%22Elyazar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lenny%22%2C%22lastName%22%3A%22Ekawati%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stefan%22%2C%22lastName%22%3A%22Jansen%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Richard%22%2C%22lastName%22%3A%22Nduwayezu%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Charisse%22%2C%22lastName%22%3A%22Garcia%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jeffrey%22%2C%22lastName%22%3A%22Plum%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jacqueline%22%2C%22lastName%22%3A%22Brenner%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Miranda%22%2C%22lastName%22%3A%22Song%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Emily%22%2C%22lastName%22%3A%22Ricotta%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Clifton%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22C.%20Louise%22%2C%22lastName%22%3A%22Thwaites%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Bradford%22%2C%22lastName%22%3A%22Wood%22%7D%5D%2C%22abstractNote%22%3A%22Introduction%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Artificial%20intelligence%20%28AI%29%20models%20trained%20on%20audio%20data%20may%20have%20the%20potential%20to%20rapidly%20perform%20clinical%20tasks%2C%20enhancing%20medical%20decision-making%20and%20potentially%20improving%20outcomes%20through%20early%20detection.%20Existing%20technologies%20depend%20on%20limited%20datasets%20collected%20with%20expensive%20recording%20equipment%20in%20high-income%20countries%2C%20which%20challenges%20deployment%20in%20resource-constrained%2C%20high-volume%20settings%20where%20audio%20data%20may%20have%20a%20profound%20impact%20on%20health%20equity.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Methods%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20This%20report%20introduces%20a%20novel%20protocol%20for%20audio%20data%20collection%20and%20a%20corresponding%20application%20that%20captures%20health%20information%20through%20guided%20questions.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Results%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20To%20demonstrate%20the%20potential%20of%20Voice%20EHR%20as%20a%20biomarker%20of%20health%2C%20initial%20experiments%20on%20data%20quality%20and%20multiple%20case%20studies%20are%20presented%20in%20this%20report.%20Large%20language%20models%20%28LLMs%29%20were%20used%20to%20compare%20transcribed%20Voice%20EHR%20data%20with%20data%20%28from%20the%20same%20patients%29%20collected%20through%20conventional%20techniques%20like%20multiple%20choice%20questions.%20Information%20contained%20in%20the%20Voice%20EHR%20samples%20was%20consistently%20rated%20as%20equally%20or%20more%20relevant%20to%20a%20health%20evaluation.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Discussion%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20The%20HEAR%20application%20facilitates%20the%20collection%20of%20an%20audio%20electronic%20health%20record%20%28%5Cu201cVoice%20EHR%5Cu201d%29%20that%20may%20contain%20complex%20biomarkers%20of%20health%20from%20conventional%20voice%5C%2Frespiratory%20features%2C%20speech%20patterns%2C%20and%20spoken%20language%20with%20semantic%20meaning%20and%20longitudinal%20context%5Cu2013potentially%20compensating%20for%20the%20typical%20limitations%20of%20unimodal%20clinical%20datasets.%22%2C%22date%22%3A%222025-1-28%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffdgth.2024.1448351%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Farticles%5C%2F10.3389%5C%2Ffdgth.2024.1448351%5C%2Ffull%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-253X%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222026-07-16T21%3A08%3A14Z%22%7D%7D%2C%7B%22key%22%3A%22VMKU28YH%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Rincon%20et%20al.%22%2C%22parsedDate%22%3A%222025%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BRincon%2C%20J.%2C%20Pelletier%2C%20A.%20R.%2C%20Gilliland%2C%20D.%2C%20Wang%2C%20W.%2C%20Wang%2C%20D.%2C%20Sankar%2C%20B.%20S.%2C%20Scott-Sheldon%2C%20L.%2C%20Gebreab%2C%20S.%2C%20Hersh%2C%20W.%2C%20Rashidi%2C%20P.%2C%20Baxter%2C%20S.%2C%20Schulz%2C%20W.%2C%20Ideker%2C%20T.%2C%20Bensoussan%2C%20Y.%2C%20Boutros%2C%20P.%20C.%2C%20Bui%2C%20A.%20A.%20T.%2C%20Walsh%2C%20C.%2C%20Watson%2C%20K.%20E.%2C%20%26amp%3B%20Ping%2C%20P.%20%282025%29.%20%26lt%3Bi%26gt%3BBridge2AI%3A%20Building%20A%20Cross-disciplinary%20Curriculum%20Towards%20AI-Enhanced%20Biomedical%20and%20Clinical%20Care%26lt%3B%5C%2Fi%26gt%3B.%20arXiv.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.48550%5C%2FARXIV.2505.14757%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.48550%5C%2FARXIV.2505.14757%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22preprint%22%2C%22title%22%3A%22Bridge2AI%3A%20Building%20A%20Cross-disciplinary%20Curriculum%20Towards%20AI-Enhanced%20Biomedical%20and%20Clinical%20Care%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22John%22%2C%22lastName%22%3A%22Rincon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexander%20R.%22%2C%22lastName%22%3A%22Pelletier%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Destiny%22%2C%22lastName%22%3A%22Gilliland%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wei%22%2C%22lastName%22%3A%22Wang%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ding%22%2C%22lastName%22%3A%22Wang%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Baradwaj%20S.%22%2C%22lastName%22%3A%22Sankar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lori%22%2C%22lastName%22%3A%22Scott-Sheldon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Samson%22%2C%22lastName%22%3A%22Gebreab%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22William%22%2C%22lastName%22%3A%22Hersh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Parisa%22%2C%22lastName%22%3A%22Rashidi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Sally%22%2C%22lastName%22%3A%22Baxter%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Wade%22%2C%22lastName%22%3A%22Schulz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Trey%22%2C%22lastName%22%3A%22Ideker%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Paul%20C.%22%2C%22lastName%22%3A%22Boutros%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alex%20A.%20T.%22%2C%22lastName%22%3A%22Bui%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Colin%22%2C%22lastName%22%3A%22Walsh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Karol%20E.%22%2C%22lastName%22%3A%22Watson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Peipei%22%2C%22lastName%22%3A%22Ping%22%7D%5D%2C%22abstractNote%22%3A%22Objective%3A%20As%20AI%20becomes%20increasingly%20central%20to%20healthcare%2C%20there%20is%20a%20pressing%20need%20for%20bioinformatics%20and%20biomedical%20training%20systems%20that%20are%20personalized%20and%20adaptable.%20Materials%20and%20Methods%3A%20The%20NIH%20Bridge2AI%20Training%2C%20Recruitment%2C%20and%20Mentoring%20%28TRM%29%20Working%20Group%20developed%20a%20cross-disciplinary%20curriculum%20grounded%20in%20collaborative%20innovation%2C%20ethical%20data%20stewardship%2C%20and%20professional%20development%20within%20an%20adapted%20Learning%20Health%20System%20%28LHS%29%20framework.%20Results%3A%20The%20curriculum%20integrates%20foundational%20AI%20modules%2C%20real-world%20projects%2C%20and%20a%20structured%20mentee-mentor%20network%20spanning%20Bridge2AI%20Grand%20Challenges%20and%20the%20Bridge%20Center.%20Guided%20by%20six%20learner%20personas%2C%20the%20program%20tailors%20educational%20pathways%20to%20individual%20needs%20while%20supporting%20scalability.%20Discussion%3A%20Iterative%20refinement%20driven%20by%20continuous%20feedback%20ensures%20that%20content%20remains%20responsive%20to%20learner%20progress%20and%20emerging%20trends.%20Conclusion%3A%20With%20over%2030%20scholars%20and%20100%20mentors%20engaged%20across%20North%20America%2C%20the%20TRM%20model%20demonstrates%20how%20adaptive%2C%20persona-informed%20training%20can%20build%20interdisciplinary%20competencies%20and%20foster%20an%20integrative%2C%20ethically%20grounded%20AI%20education%20in%20biomedical%20contexts.%22%2C%22genre%22%3A%22%22%2C%22repository%22%3A%22arXiv%22%2C%22archiveID%22%3A%22%22%2C%22date%22%3A%222025%22%2C%22DOI%22%3A%2210.48550%5C%2FARXIV.2505.14757%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Farxiv.org%5C%2Fabs%5C%2F2505.14757%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-07-20T17%3A59%3A02Z%22%7D%7D%2C%7B%22key%22%3A%227N5KU6N5%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Patel%20et%20al.%22%2C%22parsedDate%22%3A%222024-12-03%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BPatel%2C%20R.%2C%20Price%2C%20N.%2C%20Bahr%2C%20R.%2C%20Bedrick%2C%20S.%2C%20Bensoussan%2C%20Y.%2C%20B%26%23xE9%3Blisle-Pipon%2C%20J.-C.%2C%20Dorr%2C%20D.%2C%20Jackson%2C%20C.%2C%20Krussel%2C%20A.%2C%20Salvi%20Cruz%2C%20S.%2C%20Toghranegar%2C%20J.%2C%20Watts%2C%20S.%2C%20Zhao%2C%20R.%2C%20The%20Bridge2AI-Voice%20Consortium%2C%20%26amp%3B%20Powell%2C%20M.%20%282024%29.%20Summary%20of%20Keynote%20Speeches%20from%20the%202024%20Voice%20AI%20Symposium%2C%20presented%20by%20the%20Bridge2AI-Voice%20Consortium.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Digital%20Health%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B6%26lt%3B%5C%2Fi%26gt%3B%2C%201484503.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2024.1484503%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2024.1484503%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Summary%20of%20Keynote%20Speeches%20from%20the%202024%20Voice%20AI%20Symposium%2C%20presented%20by%20the%20Bridge2AI-Voice%20Consortium%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rupal%22%2C%22lastName%22%3A%22Patel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nicholson%22%2C%22lastName%22%3A%22Price%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ruth%22%2C%22lastName%22%3A%22Bahr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Bedrick%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Christophe%22%2C%22lastName%22%3A%22B%5Cu00e9lisle-Pipon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Dorr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christie%22%2C%22lastName%22%3A%22Jackson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andrea%22%2C%22lastName%22%3A%22Krussel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Samantha%22%2C%22lastName%22%3A%22Salvi%20Cruz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jamie%22%2C%22lastName%22%3A%22Toghranegar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stephanie%22%2C%22lastName%22%3A%22Watts%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Robin%22%2C%22lastName%22%3A%22Zhao%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22The%20Bridge2AI-Voice%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maria%22%2C%22lastName%22%3A%22Powell%22%7D%5D%2C%22abstractNote%22%3A%22Introduction%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20The%202024%20Voice%20AI%20Symposium%2C%20hosted%20by%20the%20Bridge2AI-Voice%20Consortium%20in%20Tampa%2C%20FL%2C%20featured%20two%20keynote%20speeches%20that%20addressed%20the%20intersection%20of%20voice%20AI%2C%20healthcare%2C%20ethics%2C%20and%20law.%20Dr.%20Rupal%20Patel%20and%20Dr.%20Nicholson%20Price%20provided%20insights%20into%20the%20advancements%2C%20applications%2C%20and%20challenges%20of%20AI-driven%20voice%20tools%20in%20healthcare.%20The%20symposium%20aimed%20to%20advance%20cross-disciplinary%20collaboration%20and%20establish%20frameworks%20for%20the%20ethical%20use%20of%20AI%20technologies%20in%20healthcare.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Methods%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20The%20keynote%20speeches%2C%20delivered%20on%20May%201st%20and%202nd%2C%20were%2030%5Cu2005minutes%20each%2C%20followed%20by%2010-minutes%20Q%26amp%3BA%20sessions.%20The%20audio%20was%20recorded%20and%20transcribed%20using%20Whisper%20%28v7.13.1%29.%20Content%20summaries%20were%20generated%20with%20the%20aid%20of%20ChatGPT%20%28v4.0%29%2C%20and%20the%20authors%20reviewed%20and%20edited%20the%20final%20transcripts%20to%20ensure%20accuracy%20and%20clarity.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Results%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Dr.%20Rupal%20Patel%5Cu2019s%20keynote%2C%20%5Cu201cReflections%20and%20New%20Frontiers%20in%20Voice%20AI%5Cu201d%2C%20explored%20the%20potential%20of%20voice%20AI%20for%20early%20detection%20of%20health%20conditions%2C%20monitoring%20disease%20progression%2C%20and%20promoting%20non-invasive%20global%20health%20management.%20She%20highlighted%20innovative%20uses%20beyond%20traditional%20applications%2C%20such%20as%20examining%20menopause-related%20symptoms.%20Dr.%20Nicholson%20Price%5Cu2019s%20keynote%2C%20%5Cu201cGovernance%20for%20Clinical%20Voice%20AI%5Cu201d%2C%20addressed%20the%20regulatory%20and%20ethical%20challenges%20posed%20by%20AI%20in%20healthcare.%20He%20stressed%20the%20need%20for%20context-aware%20systems%20and%20dynamic%20legal%20frameworks%20to%20address%20liability%20and%20accountability.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Conclusions%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20The%202024%20Voice%20AI%20Symposium%20highlighted%20the%20transformative%20potential%20of%20voice%20AI%20for%20early%20detection%2C%20health%20monitoring%2C%20and%20reducing%20healthcare%20disparities.%20It%20also%20underscored%20the%20importance%20of%20dynamic%20governance%20to%20address%20the%20ethical%20and%20regulatory%20challenges%20of%20deploying%20AI%20in%20clinical%20settings.%22%2C%22date%22%3A%222024-12-3%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffdgth.2024.1484503%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Farticles%5C%2F10.3389%5C%2Ffdgth.2024.1484503%5C%2Ffull%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-253X%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-07-20T18%3A07%3A39Z%22%7D%7D%2C%7B%22key%22%3A%22DT928PTS%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Fagherazzi%20and%20Bensoussan%22%2C%22parsedDate%22%3A%222024-11-13%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BFagherazzi%2C%20G.%2C%20%26amp%3B%20Bensoussan%2C%20Y.%20%282024%29.%20The%20Imperative%20of%20Voice%20Data%20Collection%20in%20Clinical%20Trials.%20%26lt%3Bi%26gt%3BDigital%20Biomarkers%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B8%26lt%3B%5C%2Fi%26gt%3B%281%29%2C%20207%26%23x2013%3B209.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1159%5C%2F000541456%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1159%5C%2F000541456%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22The%20Imperative%20of%20Voice%20Data%20Collection%20in%20Clinical%20Trials%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Guy%22%2C%22lastName%22%3A%22Fagherazzi%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ya%5Cu00ebl%22%2C%22lastName%22%3A%22Bensoussan%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222024-11-13%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1159%5C%2F000541456%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fkarger.com%5C%2Farticle%5C%2Fdoi%5C%2F10.1159%5C%2F000541456%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222504-110X%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222026-07-30T13%3A46%3A27Z%22%7D%7D%2C%7B%22key%22%3A%22K7ZUMUE8%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Anibal%20et%20al.%22%2C%22parsedDate%22%3A%222024-11-11%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BAnibal%2C%20J.%2C%20Gunkel%2C%20J.%2C%20Awan%2C%20S.%2C%20Huth%2C%20H.%2C%20Nguyen%2C%20H.%2C%20Le%2C%20T.%2C%20B%26%23xE9%3Blisle-Pipon%2C%20J.-C.%2C%20Boyer%2C%20M.%2C%20Hazen%2C%20L.%2C%20Bensoussan%2C%20Y.%2C%20Clifton%2C%20D.%2C%20%26amp%3B%20Wood%2C%20B.%20%282024%29.%20The%20doctor%20will%20polygraph%20you%20now%3A%20ethical%20concerns%20with%20AI%20for%20fact-checking%20patients.%20%26lt%3Bi%26gt%3BArXiv%26lt%3B%5C%2Fi%26gt%3B%2C%20arXiv%3A2408.07896v2.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fwww.ncbi.nlm.nih.gov%5C%2Fpmc%5C%2Farticles%5C%2FPMC11468487%5C%2F%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fwww.ncbi.nlm.nih.gov%5C%2Fpmc%5C%2Farticles%5C%2FPMC11468487%5C%2F%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22The%20doctor%20will%20polygraph%20you%20now%3A%20ethical%20concerns%20with%20AI%20for%20fact-checking%20patients%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22James%22%2C%22lastName%22%3A%22Anibal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jasmine%22%2C%22lastName%22%3A%22Gunkel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shaheen%22%2C%22lastName%22%3A%22Awan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hannah%22%2C%22lastName%22%3A%22Huth%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hang%22%2C%22lastName%22%3A%22Nguyen%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tram%22%2C%22lastName%22%3A%22Le%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Christophe%22%2C%22lastName%22%3A%22B%5Cu00e9lisle-Pipon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Micah%22%2C%22lastName%22%3A%22Boyer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lindsey%22%2C%22lastName%22%3A%22Hazen%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Clifton%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Bradford%22%2C%22lastName%22%3A%22Wood%22%7D%5D%2C%22abstractNote%22%3A%22Artificial%20intelligence%20%28AI%29%20methods%20have%20been%20proposed%20for%20the%20prediction%20of%20social%20behaviors%20which%20could%20be%20reasonably%20understood%20from%20patient-reported%20information.%20This%20raises%20novel%20ethical%20concerns%20about%20respect%2C%20privacy%2C%20and%20control%20over%20patient%20data.%20Ethical%20concerns%20surrounding%20clinical%20AI%20systems%20for%20social%20behavior%20verification%20can%20be%20divided%20into%20two%20main%20categories%3A%20%281%29%20the%20potential%20for%20inaccuracies%5C%2Fbiases%20within%20such%20systems%2C%20and%20%282%29%20the%20impact%20on%20trust%20in%20patient-provider%20relationships%20with%20the%20introduction%20of%20automated%20AI%20systems%20for%20%5Cu201cfact-checking%5Cu201d%2C%20particularly%20in%20cases%20where%20the%20data%5C%2Fmodels%20may%20contradict%20the%20patient.%20Additionally%2C%20this%20report%20simulated%20the%20misuse%20of%20a%20verification%20system%20using%20patient%20voice%20samples%20and%20identified%20a%20potential%20LLM%20bias%20against%20patient-reported%20information%20in%20favor%20of%20multi-dimensional%20data%20and%20the%20outputs%20of%20other%20AI%20methods%20%28i.e.%2C%20%5Cu201cAI%20self-trust%5Cu201d%29.%20Finally%2C%20recommendations%20were%20presented%20for%20mitigating%20the%20risk%20that%20AI%20verification%20methods%20will%20cause%20harm%20to%20patients%20or%20undermine%20the%20purpose%20of%20the%20healthcare%20system.%22%2C%22date%22%3A%222024-11-11%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.ncbi.nlm.nih.gov%5C%2Fpmc%5C%2Farticles%5C%2FPMC11468487%5C%2F%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222331-8422%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-07-20T18%3A02%3A28Z%22%7D%7D%2C%7B%22key%22%3A%22BMZMNFDL%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Bahr%20et%20al.%22%2C%22parsedDate%22%3A%222024-10-30%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BBahr%2C%20R.%2C%20Anibal%2C%20J.%2C%20Bedrick%2C%20S.%2C%20B%26%23xE9%3Blisle-Pipon%2C%20J.-C.%2C%20Bensoussan%2C%20Y.%2C%20Blaylock%2C%20N.%2C%20Castermans%2C%20J.%2C%20Comito%2C%20K.%2C%20Dorr%2C%20D.%2C%20Hale%2C%20G.%2C%20Jackson%2C%20C.%2C%20Krussel%2C%20A.%2C%20Kuman%2C%20K.%2C%20Komarlu%2C%20A.%20R.%2C%20Lerner-Ellis%2C%20J.%2C%20Powell%2C%20M.%2C%20Ravitsky%2C%20V.%2C%20Rameau%2C%20A.%2C%20Reavis%2C%20C.%2C%20%26%23x2026%3B%20the%20Bridge2AI-Voice%20Consortium.%20%282024%29.%20Workshop%20summaries%20from%20the%202024%20voice%20AI%20symposium%2C%20presented%20by%20the%20Bridge2AI-voice%20consortium.%20%26lt%3Bi%26gt%3BFrontiers%20in%20Digital%20Health%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B6%26lt%3B%5C%2Fi%26gt%3B%2C%201484818.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2024.1484818%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3389%5C%2Ffdgth.2024.1484818%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Workshop%20summaries%20from%20the%202024%20voice%20AI%20symposium%2C%20presented%20by%20the%20Bridge2AI-voice%20consortium%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ruth%22%2C%22lastName%22%3A%22Bahr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22James%22%2C%22lastName%22%3A%22Anibal%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Bedrick%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Christophe%22%2C%22lastName%22%3A%22B%5Cu00e9lisle-Pipon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Nate%22%2C%22lastName%22%3A%22Blaylock%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Joris%22%2C%22lastName%22%3A%22Castermans%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Keith%22%2C%22lastName%22%3A%22Comito%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Dorr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Greg%22%2C%22lastName%22%3A%22Hale%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Christie%22%2C%22lastName%22%3A%22Jackson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Andrea%22%2C%22lastName%22%3A%22Krussel%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Kimberly%22%2C%22lastName%22%3A%22Kuman%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Akash%20Raj%22%2C%22lastName%22%3A%22Komarlu%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jordan%22%2C%22lastName%22%3A%22Lerner-Ellis%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maria%22%2C%22lastName%22%3A%22Powell%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Vardit%22%2C%22lastName%22%3A%22Ravitsky%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ana%5Cu00efs%22%2C%22lastName%22%3A%22Rameau%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Charlie%22%2C%22lastName%22%3A%22Reavis%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexandros%22%2C%22lastName%22%3A%22Sigaras%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Samantha%20Salvi%22%2C%22lastName%22%3A%22Cruz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jenny%22%2C%22lastName%22%3A%22Vojtech%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Megan%22%2C%22lastName%22%3A%22Urbano%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stephanie%22%2C%22lastName%22%3A%22Watts%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Robin%22%2C%22lastName%22%3A%22Zhao%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jamie%22%2C%22lastName%22%3A%22Toghranegar%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22the%20Bridge2AI-Voice%20Consortium%22%7D%5D%2C%22abstractNote%22%3A%22Introduction%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20The%202024%20Voice%20AI%20Symposium%2C%20presented%20by%20the%20Bridge2AI-Voice%20Consortium%2C%20featured%20deep-dive%20educational%20workshops%20conducted%20by%20experts%20from%20diverse%20fields%20to%20explore%20the%20latest%20advancements%20in%20voice%20biomarkers%20and%20artificial%20intelligence%20%28AI%29%20applications%20in%20healthcare.%20Through%20five%20workshops%2C%20attendees%20learned%20about%20topics%20including%20international%20standardization%20of%20vocal%20biomarker%20data%2C%20real-world%20deployment%20of%20AI%20solutions%2C%20assistive%20technologies%20for%20voice%20disorders%2C%20best%20practices%20for%20voice%20data%20collection%2C%20and%20deep%20learning%20applications%20in%20voice%20analysis.%20These%20workshops%20aimed%20to%20foster%20collaboration%20between%20academia%2C%20industry%2C%20and%20healthcare%20to%20advance%20the%20development%20and%20implementation%20of%20voice-based%20AI%20tools.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Methods%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Each%20workshop%20featured%20a%20combination%20of%20lectures%2C%20case%20studies%2C%20and%20interactive%20discussions.%20Transcripts%20of%20audio%20recordings%20were%20generated%20using%20Whisper%20%28Version%207.13.1%29%20and%20summarized%20by%20ChatGPT%20%28Version%204.0%29%2C%20then%20reviewed%20by%20the%20authors.%20The%20workshops%20covered%20various%20methodologies%2C%20from%20signal%20processing%20and%20machine%20learning%20operations%20%28MLOps%29%20to%20ethical%20concerns%20surrounding%20AI-powered%20voice%20data%20collection.%20Practical%20demonstrations%20of%20AI-driven%20tools%20for%20voice%20disorder%20management%20and%20technical%20discussions%20on%20implementing%20voice%20AI%20models%20in%20clinical%20and%20non-clinical%20settings%20provided%20attendees%20with%20hands-on%20experience.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Results%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Key%20outcomes%20included%20the%20discussion%20of%20international%20standards%20to%20unify%20stakeholders%20in%20vocal%20biomarker%20research%2C%20practical%20challenges%20in%20deploying%20AI%20solutions%20outside%20the%20laboratory%2C%20review%20of%20Bridge2AI-Voice%20data%20collection%20processes%2C%20and%20the%20potential%20of%20AI%20to%20empower%20individuals%20with%20voice%20disorders.%20Additionally%2C%20presenters%20shared%20innovations%20in%20ethical%20AI%20practices%2C%20scalable%20machine%20learning%20frameworks%2C%20and%20advanced%20data%20collection%20techniques%20using%20diverse%20voice%20datasets.%20The%20symposium%20highlighted%20the%20successful%20integration%20of%20AI%20in%20detecting%20and%20analyzing%20voice%20signals%20for%20various%20health%20applications%2C%20with%20significant%20advancements%20in%20standardization%2C%20privacy%2C%20and%20clinical%20validation%20processes.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Discussion%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20The%20symposium%20underscored%20the%20importance%20of%20interdisciplinary%20collaboration%20to%20address%20the%20technical%2C%20ethical%2C%20and%20clinical%20challenges%20in%20the%20field%20of%20voice%20biomarkers.%20While%20AI%20models%20have%20shown%20promise%20in%20analyzing%20voice%20data%2C%20challenges%20such%20as%20data%20variability%2C%20security%2C%20and%20scalability%20remain.%20Future%20efforts%20must%20focus%20on%20refining%20data%20collection%20standards%2C%20advancing%20ethical%20AI%20practices%2C%20and%20ensuring%20diverse%20dataset%20inclusion%20to%20improve%20model%20robustness.%20By%20fostering%20collaboration%20among%20researchers%2C%20clinicians%2C%20and%20technologists%2C%20the%20symposium%20laid%20a%20foundation%20for%20future%20innovations%20in%20AI-driven%20voice%20analysis%20for%20healthcare%20diagnostics%20and%20treatment.%22%2C%22date%22%3A%222024-10-30%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3389%5C%2Ffdgth.2024.1484818%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.frontiersin.org%5C%2Farticles%5C%2F10.3389%5C%2Ffdgth.2024.1484818%5C%2Ffull%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222673-253X%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-07-20T18%3A07%3A56Z%22%7D%7D%2C%7B%22key%22%3A%229L6W9NW7%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Evangelista%20and%20Bensoussan%22%2C%22parsedDate%22%3A%222024-10-01%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BEvangelista%2C%20E.%2C%20%26amp%3B%20Bensoussan%2C%20Y.%20%282024%29.%20Standardization%2C%20Collaboration%2C%20and%20Education%20in%20the%20Implementation%20of%20Artificial%20Intelligence%20in%20Otolaryngology%3A%20The%20Key%20to%20Scalable%20Impact.%20%26lt%3Bi%26gt%3BOtolaryngologic%20Clinics%20of%20North%20America%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B57%26lt%3B%5C%2Fi%26gt%3B%285%29%2C%20897%26%23x2013%3B908.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.otc.2024.04.005%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.otc.2024.04.005%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Standardization%2C%20Collaboration%2C%20and%20Education%20in%20the%20Implementation%20of%20Artificial%20Intelligence%20in%20Otolaryngology%3A%20The%20Key%20to%20Scalable%20Impact%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Emily%22%2C%22lastName%22%3A%22Evangelista%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%222024-10-01%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.otc.2024.04.005%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.oto.theclinics.com%5C%2Farticle%5C%2FS0030-6665%2824%2900063-X%5C%2Fabstract%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%220030-6665%2C%201557-8259%22%2C%22language%22%3A%22English%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222024-10-18T15%3A50%3A23Z%22%7D%7D%2C%7B%22key%22%3A%22PKDMMYRS%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Awan%20et%20al.%22%2C%22parsedDate%22%3A%222024-09-20%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BAwan%2C%20S.%20N.%2C%20Bahr%2C%20R.%2C%20Watts%2C%20S.%2C%20Boyer%2C%20M.%2C%20Budinsky%2C%20R.%2C%20%26amp%3B%20Bensoussan%2C%20Y.%20%282024%29.%20Evidence-Based%20Recommendations%20for%20Tablet%20Recordings%20From%20the%20Bridge2AI-Voice%20Acoustic%20Experiments.%20%26lt%3Bi%26gt%3BJournal%20of%20Voice%26lt%3B%5C%2Fi%26gt%3B.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.jvoice.2024.08.029%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1016%5C%2Fj.jvoice.2024.08.029%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Evidence-Based%20Recommendations%20for%20Tablet%20Recordings%20From%20the%20Bridge2AI-Voice%20Acoustic%20Experiments%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shaheen%20N.%22%2C%22lastName%22%3A%22Awan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ruth%22%2C%22lastName%22%3A%22Bahr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stephanie%22%2C%22lastName%22%3A%22Watts%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Micah%22%2C%22lastName%22%3A%22Boyer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Robert%22%2C%22lastName%22%3A%22Budinsky%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%5D%2C%22abstractNote%22%3A%22Background%5CnAs%20part%20of%20a%20larger%20goal%20to%20create%20best%20practices%20for%20voice%20data%20collection%20to%20fuel%20voice%20artificial%20intelligence%20%28AI%29%20research%2C%20the%20objective%20of%20this%20study%20was%20to%20investigate%20the%20ability%20of%20readily%20available%20iOS%20and%20Android%20tablets%20with%20and%20without%20low-cost%20headset%20microphones%20to%20produce%20recordings%20and%20subsequent%20acoustic%20measures%20of%20voice%20comparable%20to%20%5Cu201cresearch%20quality%5Cu201d%20instrumentation.%5CnMethods%5CnRecordings%20of%2024%20sustained%20vowel%20samples%20representing%20a%20wide%20range%20of%20typical%20and%20disordered%20voices%20were%20played%20via%20a%20head-and-torso%20model%20and%20recorded%20using%20a%20research%20quality%20standard%20microphone%5C%2Fpreamplifier%5C%2Faudio%20interface.%20Acoustic%20measurements%20from%20the%20standard%20were%20compared%20with%20two%20popular%20tablets%20using%20their%20built-in%20microphones%20and%20with%20low-cost%20headset%20microphones%20at%20different%20distances%20from%20the%20mouth.%5CnResults%5CnVoice%20measurements%20obtained%20via%20tablets%20%2B%20headset%20microphones%20close%20to%20the%20mouth%20%282.5%20and%205%5Cu00a0cm%29%20strongly%20correlated%20%28r%5Cu2019s%5Cu00a0%26gt%3B%5Cu00a00.90%29%20with%20the%20research%20standard%20and%20resulted%20in%20no%20significant%20differences%20for%20measures%20of%20vocal%20frequency%20and%20perturbation.%20In%20contrast%2C%20voice%20measurements%20obtained%20using%20the%20tablets%5Cu2019%20built-in%20microphones%20at%20typical%20reading%20distances%20%2830%20and%2045%5Cu00a0cm%29%20tended%20to%20show%20substantial%20variability%20in%20measurement%2C%20greater%20mean%20differences%20in%20voice%20measurements%2C%20and%20relatively%20poorer%20correlations%20vs%5Cu00a0the%20standard.%5CnConclusion%5CnFindings%20from%20this%20study%20support%20preliminary%20recommendations%20from%20the%20Bridge2AI-Voice%20Consortium%20recommending%20the%20use%20of%20smartphones%20paired%20with%20low-cost%20headset%20microphones%20as%20adequate%20methods%20of%20recording%20for%20large-scale%20voice%20data%20collection%20from%20a%20variety%20of%20clinical%20and%20nonclinical%20settings.%20Compared%20with%20recording%20using%20a%20tablet%20direct%2C%20a%20headset%20microphone%20controls%20for%20recording%20distance%20and%20reduces%20the%20effects%20of%20background%20noise%2C%20resulting%20in%20decreased%20variability%20in%20recording%20quality.%5CnData%20availability%5CnData%20supporting%20the%20results%20reported%20in%20this%20article%20may%20be%20obtained%20upon%20request%20from%20the%20contact%20author.%22%2C%22date%22%3A%222024-09-20%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1016%5C%2Fj.jvoice.2024.08.029%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.sciencedirect.com%5C%2Fscience%5C%2Farticle%5C%2Fpii%5C%2FS0892199724002832%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%220892-1997%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222024-09-24T12%3A09%3A28Z%22%7D%7D%2C%7B%22key%22%3A%22Z22N8ITD%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Rameau%20et%20al.%22%2C%22parsedDate%22%3A%222024-09-01%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BRameau%2C%20A.%2C%20Ghosh%2C%20S.%2C%20Sigaras%2C%20A.%2C%20Elemento%2C%20O.%2C%20Belisle-Pipon%2C%20J.-C.%2C%20Ravitsky%2C%20V.%2C%20Powell%2C%20M.%2C%20Johnson%2C%20A.%2C%20Dorr%2C%20D.%2C%20Payne%2C%20P.%2C%20Boyer%2C%20M.%2C%20Watts%2C%20S.%2C%20Bahr%2C%20R.%2C%20Rudzicz%2C%20F.%2C%20Lerner-Ellis%2C%20J.%2C%20Awan%2C%20S.%2C%20Bolser%2C%20D.%2C%20%26amp%3B%20Bensoussan%2C%20Y.%20%282024%29.%20Developing%20Multi-Disorder%20Voice%20Protocols%3A%20A%20team%20science%20approach%20involving%20clinical%20expertise%2C%20bioethics%2C%20standards%2C%20and%20DEI.%20%26lt%3Bi%26gt%3BInterspeech%202024%26lt%3B%5C%2Fi%26gt%3B%2C%201445%26%23x2013%3B1449.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.21437%5C%2FInterspeech.2024-1926%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.21437%5C%2FInterspeech.2024-1926%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22conferencePaper%22%2C%22title%22%3A%22Developing%20Multi-Disorder%20Voice%20Protocols%3A%20A%20team%20science%20approach%20involving%20clinical%20expertise%2C%20bioethics%2C%20standards%2C%20and%20DEI.%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ana%5Cu00efs%22%2C%22lastName%22%3A%22Rameau%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Satrajit%22%2C%22lastName%22%3A%22Ghosh%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alexandros%22%2C%22lastName%22%3A%22Sigaras%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Olivier%22%2C%22lastName%22%3A%22Elemento%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean-Christophe%22%2C%22lastName%22%3A%22Belisle-Pipon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Vardit%22%2C%22lastName%22%3A%22Ravitsky%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maria%22%2C%22lastName%22%3A%22Powell%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Alistair%22%2C%22lastName%22%3A%22Johnson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22David%22%2C%22lastName%22%3A%22Dorr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Philip%22%2C%22lastName%22%3A%22Payne%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Micah%22%2C%22lastName%22%3A%22Boyer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stephanie%22%2C%22lastName%22%3A%22Watts%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ruth%22%2C%22lastName%22%3A%22Bahr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Frank%22%2C%22lastName%22%3A%22Rudzicz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jordan%22%2C%22lastName%22%3A%22Lerner-Ellis%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shaheen%22%2C%22lastName%22%3A%22Awan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Don%22%2C%22lastName%22%3A%22Bolser%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22proceedingsTitle%22%3A%22Interspeech%202024%22%2C%22conferenceName%22%3A%22Interspeech%202024%22%2C%22date%22%3A%222024-9-1%22%2C%22eventPlace%22%3A%22%22%2C%22DOI%22%3A%2210.21437%5C%2FInterspeech.2024-1926%22%2C%22ISBN%22%3A%22%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.isca-archive.org%5C%2Finterspeech_2024%5C%2Frameau24_interspeech.html%22%2C%22ISSN%22%3A%22%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222026-07-30T13%3A48%3A17Z%22%7D%7D%2C%7B%22key%22%3A%22QDCE5XF7%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Gopinathan%20et%20al.%22%2C%22parsedDate%22%3A%222024-08-10%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BGopinathan%2C%20M.%2C%20Krol%2C%20O.%2C%20Karstens%2C%20L.%2C%20Bedrick%2C%20S.%2C%20%26amp%3B%20Hersh%2C%20B.%20%282024%2C%20August%2010%29.%20%26lt%3Bi%26gt%3BVoice%20as%20a%20Biomarker%3A%20Exploratory%20Analysis%20of%20Airway%20Stenosis%26lt%3B%5C%2Fi%26gt%3B%20%5BPoster%20Presentation%5D.%20Bridge2AI-Voice%20Summer%20School%20Hackathon.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22presentation%22%2C%22title%22%3A%22Voice%20as%20a%20Biomarker%3A%20Exploratory%20Analysis%20of%20Airway%20Stenosis%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Mahathi%22%2C%22lastName%22%3A%22Gopinathan%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Olivia%22%2C%22lastName%22%3A%22Krol%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Lisa%22%2C%22lastName%22%3A%22Karstens%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Steve%22%2C%22lastName%22%3A%22Bedrick%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Bill%22%2C%22lastName%22%3A%22Hersh%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%22August%2010th%2C%202024%22%2C%22sessionTitle%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%22SSNIVE8D%22%5D%2C%22dateModified%22%3A%222025-08-27T13%3A40%3A52Z%22%7D%7D%2C%7B%22key%22%3A%22VT54536H%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Harrison%20et%20al.%22%2C%22parsedDate%22%3A%222024-08-10%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BHarrison%2C%20R.%2C%20Jenkins%2C%20P.%2C%20Karstens%2C%20L.%2C%20Bedrick%2C%20S.%2C%20%26amp%3B%20Hersh%2C%20B.%20%282024%2C%20August%2010%29.%20%26lt%3Bi%26gt%3BVoice%20as%20a%20Biomarker%3A%20Exploratory%20Analysis%20for%20Benign%20and%20Malignant%20Vocal%20Fold%20Lesions%26lt%3B%5C%2Fi%26gt%3B%20%5BPoster%20Presentation%5D.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22presentation%22%2C%22title%22%3A%22Voice%20as%20a%20Biomarker%3A%20Exploratory%20Analysis%20for%20Benign%20and%20Malignant%20Vocal%20Fold%20Lesions%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Rylan%22%2C%22lastName%22%3A%22Harrison%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Phillip%22%2C%22lastName%22%3A%22Jenkins%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Lisa%22%2C%22lastName%22%3A%22Karstens%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Steven%22%2C%22lastName%22%3A%22Bedrick%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Bill%22%2C%22lastName%22%3A%22Hersh%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%22August%2010th%2C%202024%22%2C%22sessionTitle%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%22SSNIVE8D%22%5D%2C%22dateModified%22%3A%222025-08-27T13%3A44%3A11Z%22%7D%7D%2C%7B%22key%22%3A%22UPFDRIFX%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Jang%20et%20al.%22%2C%22parsedDate%22%3A%222024-08-10%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BJang%2C%20D.%2C%20Babatunde%2C%20A.%2C%20%26amp%3B%20Lu%2C%20E.%20%282024%2C%20August%2010%29.%20%26lt%3Bi%26gt%3BPreliminary%20Dataset%20Exploration%20of%20Hypertension%20Voice%20Biomarkers%26lt%3B%5C%2Fi%26gt%3B%20%5BPoster%20Presentation%5D.%20Bridge2AI-Voice%20Summer%20School%20Hackathon.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22presentation%22%2C%22title%22%3A%22Preliminary%20Dataset%20Exploration%20of%20Hypertension%20Voice%20Biomarkers%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Dan%22%2C%22lastName%22%3A%22Jang%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Ayo%22%2C%22lastName%22%3A%22Babatunde%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Eileen%22%2C%22lastName%22%3A%22Lu%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%22August%2010th%2C%202024%22%2C%22sessionTitle%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%22SSNIVE8D%22%5D%2C%22dateModified%22%3A%222025-08-27T13%3A42%3A32Z%22%7D%7D%2C%7B%22key%22%3A%22MWGHC8X5%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Kapoor%20et%20al.%22%2C%22parsedDate%22%3A%222024-08-10%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BKapoor%2C%20U.%2C%20Chaitanya%20Nama%2C%20G.%20K.%2C%20%26amp%3B%20Khorrami%2C%20P.%20%282024%2C%20August%2010%29.%20%26lt%3Bi%26gt%3BOptimized%20Preprocessing%20Steps%20and%20Neural%20Network%20Parameters%20for%20Generalized%20Stridor%20Detection%20and%20Characterization%26lt%3B%5C%2Fi%26gt%3B%20%5BPoster%20Presentation%5D.%20Bridge2AI-Voice%20Summer%20School%20Hackathon.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22presentation%22%2C%22title%22%3A%22Optimized%20Preprocessing%20Steps%20and%20Neural%20Network%20Parameters%20for%20Generalized%20Stridor%20Detection%20and%20Characterization%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Utsav%22%2C%22lastName%22%3A%22Kapoor%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Geetha%20Krishna%22%2C%22lastName%22%3A%22Chaitanya%20Nama%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Parsa%22%2C%22lastName%22%3A%22Khorrami%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%22August%2010th%2C%202024%22%2C%22sessionTitle%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%22SSNIVE8D%22%5D%2C%22dateModified%22%3A%222025-08-27T13%3A52%3A19Z%22%7D%7D%2C%7B%22key%22%3A%22YFQNCLDM%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Luu%20and%20Olivio%20Cauberghs%22%2C%22parsedDate%22%3A%222024-08-10%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BLuu%2C%20M.%2C%20%26amp%3B%20Olivio%20Cauberghs%2C%20E.%20%282024%2C%20August%2010%29.%20%26lt%3Bi%26gt%3BIdentifying%20Biomarkers%20of%20Unilateral%20Vocal%20Fold%20Paralysis%20for%20Artificial%20Intelligence%20%26amp%3B%20Machine%20Learning%20Development%26lt%3B%5C%2Fi%26gt%3B%20%5BPoster%20Presentation%5D.%20Bridge2AI-Voice%20Summer%20School%20Hackathon.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22presentation%22%2C%22title%22%3A%22Identifying%20Biomarkers%20of%20Unilateral%20Vocal%20Fold%20Paralysis%20for%20Artificial%20Intelligence%20%26%20Machine%20Learning%20Development%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Madeline%22%2C%22lastName%22%3A%22Luu%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Emiliano%22%2C%22lastName%22%3A%22Olivio%20Cauberghs%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%22August%2010th%2C%202024%22%2C%22sessionTitle%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%22SSNIVE8D%22%5D%2C%22dateModified%22%3A%222025-08-27T13%3A39%3A11Z%22%7D%7D%2C%7B%22key%22%3A%223S3HAQ3H%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Margolis%20et%20al.%22%2C%22parsedDate%22%3A%222024-08-10%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BMargolis%2C%20H.%2C%20Mathur%2C%20A.%2C%20%26amp%3B%20Rashkovich%2C%20S.%20%282024%2C%20August%2010%29.%20%26lt%3Bi%26gt%3BDisease%20Classification%20with%20Voice%20Biomarkers%3A%20Identifying%20Depression%20and%20Anxiety%26lt%3B%5C%2Fi%26gt%3B%20%5BPoster%20Presentation%5D.%20Bridge2AI-Voice%20Summer%20School%20Hackathon.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22presentation%22%2C%22title%22%3A%22Disease%20Classification%20with%20Voice%20Biomarkers%3A%20Identifying%20Depression%20and%20Anxiety%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Hudson%22%2C%22lastName%22%3A%22Margolis%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Aarush%22%2C%22lastName%22%3A%22Mathur%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Sam%22%2C%22lastName%22%3A%22Rashkovich%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%22August%2010th%2C%202024%22%2C%22sessionTitle%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%22SSNIVE8D%22%5D%2C%22dateModified%22%3A%222025-08-27T13%3A35%3A38Z%22%7D%7D%2C%7B%22key%22%3A%222YURRIZL%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Power%20and%20Kyeremateng%22%2C%22parsedDate%22%3A%222024-08-10%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BPower%2C%20W.%2C%20%26amp%3B%20Kyeremateng%2C%20I.%20%282024%2C%20August%2010%29.%20%26lt%3Bi%26gt%3BDepression%20Prediction%20using%20Machine%20Learning%20with%20Clinical%20and%20Audio%20Data%20from%20the%20Bridge2AI%20Voice%20Project%26lt%3B%5C%2Fi%26gt%3B%20%5BPoster%20Presentation%5D.%20Bridge2AI-Voice%20Summer%20School%20Hackathon.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22presentation%22%2C%22title%22%3A%22Depression%20Prediction%20using%20Machine%20Learning%20with%20Clinical%20and%20Audio%20Data%20from%20the%20Bridge2AI%20Voice%20Project%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Will%22%2C%22lastName%22%3A%22Power%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Isaac%22%2C%22lastName%22%3A%22Kyeremateng%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%22August%2010th%2C%202024%22%2C%22sessionTitle%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%22SSNIVE8D%22%5D%2C%22dateModified%22%3A%222025-08-27T13%3A45%3A29Z%22%7D%7D%2C%7B%22key%22%3A%22A3NJIU8Z%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Schimmelpfennig%20et%20al.%22%2C%22parsedDate%22%3A%222024-08-10%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BSchimmelpfennig%2C%20L.%2C%20Keshariya%2C%20A.%2C%20%26amp%3B%20Abrams%2C%20Z.%20%282024%2C%20August%2010%29.%20%26lt%3Bi%26gt%3BAirway%20Stenosis%20Classification%20With%20Breathing%20Audio%20Data%26lt%3B%5C%2Fi%26gt%3B%20%5BPoster%20Presentation%5D.%20Bridge2AI-Voice%20Summer%20School%20Hackathon.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22presentation%22%2C%22title%22%3A%22Airway%20Stenosis%20Classification%20With%20Breathing%20Audio%20Data%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Lars%22%2C%22lastName%22%3A%22Schimmelpfennig%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Ashi%22%2C%22lastName%22%3A%22Keshariya%22%7D%2C%7B%22creatorType%22%3A%22presenter%22%2C%22firstName%22%3A%22Zachary%22%2C%22lastName%22%3A%22Abrams%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22date%22%3A%22August%2010th%2C%202024%22%2C%22sessionTitle%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%22SSNIVE8D%22%5D%2C%22dateModified%22%3A%222025-08-27T13%3A53%3A32Z%22%7D%7D%2C%7B%22key%22%3A%22SNUDW6LS%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Awan%20et%20al.%22%2C%22parsedDate%22%3A%222024-06-06%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BAwan%2C%20S.%20N.%2C%20Bahr%2C%20R.%2C%20Watts%2C%20S.%2C%20Boyer%2C%20M.%2C%20Budinsky%2C%20R.%2C%20Bridge2AI%20Voice%20Consortium%2C%20%26amp%3B%20Bensoussan%2C%20Y.%20%282024%29.%20Validity%20of%20Acoustic%20Measures%20Obtained%20Using%20Various%20Recording%20Methods%20Including%20Smartphones%20With%20and%20Without%20Headset%20Microphones.%20%26lt%3Bi%26gt%3BJournal%20of%20Speech%2C%20Language%2C%20and%20Hearing%20Research%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B67%26lt%3B%5C%2Fi%26gt%3B%286%29%2C%201712%26%23x2013%3B1730.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1044%5C%2F2024_JSLHR-23-00759%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1044%5C%2F2024_JSLHR-23-00759%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Validity%20of%20Acoustic%20Measures%20Obtained%20Using%20Various%20Recording%20Methods%20Including%20Smartphones%20With%20and%20Without%20Headset%20Microphones%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Shaheen%20N.%22%2C%22lastName%22%3A%22Awan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ruth%22%2C%22lastName%22%3A%22Bahr%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stephanie%22%2C%22lastName%22%3A%22Watts%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Micah%22%2C%22lastName%22%3A%22Boyer%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Robert%22%2C%22lastName%22%3A%22Budinsky%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22Bridge2AI%20Voice%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%5D%2C%22abstractNote%22%3A%22Purpose%3A%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20The%20goal%20of%20this%20study%20was%20to%20assess%20various%20recording%20methods%2C%20including%20combinations%20of%20high-%20versus%20low-cost%20microphones%2C%20recording%20interfaces%2C%20and%20smartphones%20in%20terms%20of%20their%20ability%20to%20produce%20commonly%20used%20time-%20and%20spectral-based%20voice%20measurements.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Method%3A%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Twenty-four%20vowel%20samples%20representing%20a%20diversity%20of%20voice%20quality%20deviations%20and%20severities%20from%20a%20wide%20age%20range%20of%20male%20and%20female%20speakers%20were%20played%20via%20a%20head-and-thorax%20model%20and%20recorded%20using%20a%20high-cost%2C%20research%20standard%20GRAS%2040AF%20%28GRAS%20Sound%20%26amp%3B%20Vibration%29%20microphone%20and%20amplification%20system.%20Additional%20recordings%20were%20made%20using%20various%20combinations%20of%20headset%20microphones%20%28AKG%20C555%20L%20%5BAKG%20Acoustics%20GmbH%5D%2C%20Shure%20SM35-XLR%20%5BShure%20Incorporated%5D%2C%20AVID%20AE-36%20%5BAVID%20Products%2C%20Inc.%5D%29%20and%20audio%20interfaces%20%28Focusrite%20Scarlett%202i2%20%5BFocusrite%20Audio%20Engineering%20Ltd.%5D%20and%20PC%2C%20Focusrite%20and%20smartphone%2C%20smartphone%20via%20a%20TRRS%20adapter%29%2C%20as%20well%20as%20smartphones%20direct%20%28Apple%20iPhone%2013%20Pro%2C%20Google%20Pixel%206%29%20using%20their%20built-in%20microphones.%20The%20effect%20of%20background%20noise%20from%20four%20different%20room%20conditions%20was%20also%20evaluated.%20Vowel%20samples%20were%20analyzed%20for%20measures%20of%20fundamental%20frequency%2C%20perturbation%2C%20cepstral%20peak%20prominence%2C%20and%20spectral%20tilt%20%28low%20vs.%20high%20spectral%20ratio%29.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Results%3A%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20Results%20show%20that%20a%20wide%20variety%20of%20recording%20methods%2C%20including%20smartphones%20with%20and%20without%20a%20low-cost%20headset%20microphone%2C%20can%20effectively%20track%20the%20wide%20range%20of%20acoustic%20characteristics%20in%20a%20diverse%20set%20of%20typical%20and%20disordered%20voice%20samples.%20Although%20significant%20differences%20in%20acoustic%20measures%20of%20voice%20may%20be%20observed%2C%20the%20presence%20of%20extremely%20strong%20correlations%20%28%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20r%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20s%20%26gt%3B%20.90%29%20with%20the%20recording%20standard%20implies%20a%20strong%20linear%20relationship%20between%20the%20results%20of%20different%20methods%20that%20may%20be%20used%20to%20predict%20and%20adjust%20any%20observed%20differences%20in%20measurement%20results.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Conclusion%3A%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Because%20handheld%20smartphone%20distance%20and%20positioning%20may%20be%20highly%20variable%20when%20used%20in%20actual%20clinical%20recording%20situations%2C%20smartphone%20%2B%20a%20low-cost%20headset%20microphone%20is%20recommended%20as%20an%20affordable%20recording%20method%20that%20controls%20mouth-to-microphone%20distance%20and%20positioning%20and%20allows%20both%20hands%20to%20be%20available%20for%20manipulation%20of%20the%20smartphone%20device.%22%2C%22date%22%3A%222024-06-06%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1044%5C%2F2024_JSLHR-23-00759%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fpubs.asha.org%5C%2Fdoi%5C%2F10.1044%5C%2F2024_JSLHR-23-00759%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%221092-4388%2C%201558-9102%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222026-07-16T21%3A14%3A53Z%22%7D%7D%2C%7B%22key%22%3A%22RZMP6HDD%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Rogers%20et%20al.%22%2C%22parsedDate%22%3A%222024-06%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BRogers%2C%20H.%20P.%2C%20Hseu%2C%20A.%2C%20Kim%2C%20J.%2C%20Silberholz%2C%20E.%2C%20Jo%2C%20S.%2C%20Dorste%2C%20A.%2C%20%26amp%3B%20Jenkins%2C%20K.%20%282024%29.%20Voice%20as%20a%20Biomarker%20of%20Pediatric%20Health%3A%20A%20Scoping%20Review.%20%26lt%3Bi%26gt%3BChildren%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B11%26lt%3B%5C%2Fi%26gt%3B%286%29%2C%20684.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3390%5C%2Fchildren11060684%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.3390%5C%2Fchildren11060684%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Voice%20as%20a%20Biomarker%20of%20Pediatric%20Health%3A%20A%20Scoping%20Review%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hannah%20Paige%22%2C%22lastName%22%3A%22Rogers%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anne%22%2C%22lastName%22%3A%22Hseu%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jung%22%2C%22lastName%22%3A%22Kim%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Elizabeth%22%2C%22lastName%22%3A%22Silberholz%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stacy%22%2C%22lastName%22%3A%22Jo%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anna%22%2C%22lastName%22%3A%22Dorste%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Kathy%22%2C%22lastName%22%3A%22Jenkins%22%7D%5D%2C%22abstractNote%22%3A%22The%20human%20voice%20has%20the%20potential%20to%20serve%20as%20a%20valuable%20biomarker%20for%20the%20early%20detection%2C%20diagnosis%2C%20and%20monitoring%20of%20pediatric%20conditions.%20This%20scoping%20review%20synthesizes%20the%20current%20knowledge%20on%20the%20application%20of%20artificial%20intelligence%20%28AI%29%20in%20analyzing%20pediatric%20voice%20as%20a%20biomarker%20for%20health.%20The%20included%20studies%20featured%20voice%20recordings%20from%20pediatric%20populations%20aged%200%5Cu201317%20years%2C%20utilized%20feature%20extraction%20methods%2C%20and%20analyzed%20pathological%20biomarkers%20using%20AI%20models.%20Data%20from%2062%20studies%20were%20extracted%2C%20encompassing%20study%20and%20participant%20characteristics%2C%20recording%20sources%2C%20feature%20extraction%20methods%2C%20and%20AI%20models.%20Data%20from%2039%20models%20across%2035%20studies%20were%20evaluated%20for%20accuracy%2C%20sensitivity%2C%20and%20specificity.%20The%20review%20showed%20a%20global%20representation%20of%20pediatric%20voice%20studies%2C%20with%20a%20focus%20on%20developmental%2C%20respiratory%2C%20speech%2C%20and%20language%20conditions.%20The%20most%20frequently%20studied%20conditions%20were%20autism%20spectrum%20disorder%2C%20intellectual%20disabilities%2C%20asphyxia%2C%20and%20asthma.%20Mel-Frequency%20Cepstral%20Coefficients%20were%20the%20most%20utilized%20feature%20extraction%20method%2C%20while%20Support%20Vector%20Machines%20were%20the%20predominant%20AI%20model.%20The%20analysis%20of%20pediatric%20voice%20using%20AI%20demonstrates%20promise%20as%20a%20non-invasive%2C%20cost-effective%20biomarker%20for%20a%20broad%20spectrum%20of%20pediatric%20conditions.%20Further%20research%20is%20necessary%20to%20standardize%20the%20feature%20extraction%20methods%20and%20AI%20models%20utilized%20for%20the%20evaluation%20of%20pediatric%20voice%20as%20a%20biomarker%20for%20health.%20Standardization%20has%20significant%20potential%20to%20enhance%20the%20accuracy%20and%20applicability%20of%20these%20tools%20in%20clinical%20settings%20across%20a%20variety%20of%20conditions%20and%20voice%20recording%20types.%20Further%20development%20of%20this%20field%20has%20enormous%20potential%20for%20the%20creation%20of%20innovative%20diagnostic%20tools%20and%20interventions%20for%20pediatric%20populations%20globally.%22%2C%22date%22%3A%222024%5C%2F6%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.3390%5C%2Fchildren11060684%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.mdpi.com%5C%2F2227-9067%5C%2F11%5C%2F6%5C%2F684%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222227-9067%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222024-06-22T23%3A44%3A03Z%22%7D%7D%2C%7B%22key%22%3A%223IGMCTMG%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Bensoussan%20et%20al.%22%2C%22parsedDate%22%3A%222024-04-01%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BBensoussan%2C%20Y.%2C%20Elemento%2C%20O.%2C%20%26amp%3B%20Rameau%2C%20A.%20%282024%29.%20Voice%20as%20an%20AI%20Biomarker%20of%20Health%26%23x2014%3BIntroducing%20Audiomics.%20%26lt%3Bi%26gt%3BJAMA%20Otolaryngology%26%23x2013%3BHead%20%26amp%3B%20Neck%20Surgery%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B150%26lt%3B%5C%2Fi%26gt%3B%284%29%2C%20283%26%23x2013%3B284.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1001%5C%2Fjamaoto.2023.4807%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1001%5C%2Fjamaoto.2023.4807%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Voice%20as%20an%20AI%20Biomarker%20of%20Health%5Cu2014Introducing%20Audiomics%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ya%5Cu00ebl%22%2C%22lastName%22%3A%22Bensoussan%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Olivier%22%2C%22lastName%22%3A%22Elemento%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Ana%5Cu00efs%22%2C%22lastName%22%3A%22Rameau%22%7D%5D%2C%22abstractNote%22%3A%22Voice%2C%20speech%2C%20and%20respiratory%20sounds%20provide%20important%20clinical%20insights%20into%20patients%5Cu2019%20health%20status.%20In%20the%20age%20of%20artificial%20intelligence%20%28AI%29%2C%20patients%5Cu2019%20audio%20recordings%20are%20being%20investigated%20as%20digital%20biomarkers%20for%20early%20detection%20of%20a%20broad%20range%20of%20conditions%2C%20including%20laryngeal%20pathology%2C%20neurological%20and%20psychological%20disorders%2C%20head%20and%20neck%20cancers%2C%20and%20diabetes.%20Besides%20neurologists%2C%20speech%20language%20pathologists%2C%20and%20internists%2C%20otolaryngologists%20also%20have%20unique%20perspectives%20and%20expertise%20on%20voice%2C%20speech%2C%20and%20respiratory%20sounds%20that%20can%20fuel%20this%20line%20of%20research%20and%20innovation.%22%2C%22date%22%3A%222024-04-01%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1001%5C%2Fjamaoto.2023.4807%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1001%5C%2Fjamaoto.2023.4807%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222168-6181%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%229VUZZA63%22%5D%2C%22dateModified%22%3A%222024-12-27T15%3A36%3A56Z%22%7D%7D%2C%7B%22key%22%3A%22KKHFI39L%22%2C%22library%22%3A%7B%22id%22%3A5285517%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Evangelista%20et%20al.%22%2C%22parsedDate%22%3A%222024%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BEvangelista%2C%20E.%20G.%2C%20B%26%23xE9%3Blisle%26%23x2010%3BPipon%2C%20J.%2C%20Naunheim%2C%20M.%20R.%2C%20Powell%2C%20M.%2C%20Gallois%2C%20H.%2C%20Bridge2AI%26%23x2010%3BVoice%20Consortium%2C%20%26amp%3B%20Bensoussan%2C%20Y.%20%282024%29.%20Voice%20as%20a%20Biomarker%20in%20Health%26%23x2010%3BTech%3A%20Mapping%20the%20Evolving%20Landscape%20of%20Voice%20Biomarkers%20in%20the%20Start%26%23x2010%3BUp%20World.%20%26lt%3Bi%26gt%3BOtolaryngology%26%23x2013%3BHead%20and%20Neck%20Surgery%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B171%26lt%3B%5C%2Fi%26gt%3B%282%29%2C%20340%26%23x2013%3B352.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fohn.830%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1002%5C%2Fohn.830%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Voice%20as%20a%20Biomarker%20in%20Health%5Cu2010Tech%3A%20Mapping%20the%20Evolving%20Landscape%20of%20Voice%20Biomarkers%20in%20the%20Start%5Cu2010Up%20World%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Emily%20G.%22%2C%22lastName%22%3A%22Evangelista%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jean%5Cu2010Christophe%22%2C%22lastName%22%3A%22B%5Cu00e9lisle%5Cu2010Pipon%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Matthew%20R.%22%2C%22lastName%22%3A%22Naunheim%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Maria%22%2C%22lastName%22%3A%22Powell%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hortense%22%2C%22lastName%22%3A%22Gallois%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22name%22%3A%22Bridge2AI%5Cu2010Voice%20Consortium%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Yael%22%2C%22lastName%22%3A%22Bensoussan%22%7D%5D%2C%22abstractNote%22%3A%22Abstract%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Objective%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20The%20vocal%20biomarkers%20market%20was%20worth%20%241.9B%20in%202021%20and%20is%20projected%20to%20exceed%20%245.1B%20by%202028%2C%20for%20a%20compound%20annual%20growth%20rate%20of%2015.15%25.%20The%20investment%20growth%20demonstrates%20a%20blossoming%20interest%20in%20voice%20and%20artificial%20intelligence%20%28AI%29%20as%20it%20relates%20to%20human%20health.%20The%20objective%20of%20this%20study%20was%20to%20map%20the%20current%20landscape%20of%20start%5Cu2010ups%20utilizing%20voice%20as%20a%20biomarker%20in%20health%5Cu2010tech.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Data%20Sources%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20A%20comprehensive%20search%20for%20start%5Cu2010ups%20was%20conducted%20using%20Google%2C%20LinkedIn%2C%20Twitter%2C%20and%20Facebook.%20A%20review%20of%20the%20research%20was%20performed%20using%20company%20website%2C%20PubMed%2C%20and%20Google%20Scholar.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Review%20Methods%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20A%203%5Cu2010pronged%20approach%20was%20taken%20to%20thoroughly%20map%20the%20landscape.%20First%2C%20an%20internet%20search%20was%20conducted%20to%20identify%20current%20start%5Cu2010ups%20focusing%20on%20products%20relating%20to%20voice%20as%20a%20biomarker%20of%20health.%20Second%2C%20Crunchbase%20was%20utilized%20to%20collect%20financial%20and%20organizational%20information.%20Third%2C%20a%20review%20of%20the%20literature%20was%20conducted%20to%20analyze%20publications%20associated%20with%20the%20identified%20start%5Cu2010ups.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Results%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20A%20total%20of%2027%20start%5Cu2010up%20start%5Cu2010ups%20with%20a%20focus%20in%20the%20utilization%20of%20AI%20for%20developing%20biomarkers%20of%20health%20from%20the%20human%20voice%20were%20identified.%20Twenty%5Cu2010four%20of%20these%20start%5Cu2010ups%20garnered%20%24178%2C808%2C039%20in%20investments.%20The%2027%20start%5Cu2010ups%20published%20194%20publications%20combined%2C%20128%20%2866%25%29%20of%20which%20were%20peer%20reviewed.%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Conclusion%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20There%20is%20growing%20enthusiasm%20surrounding%20voice%20as%20a%20biomarker%20in%20health%5Cu2010tech.%20Academic%20drive%20may%20complement%20commercialization%20to%20best%20achieve%20progress%20in%20this%20arena.%20More%20research%20is%20needed%20to%20accurately%20capture%20the%20entirety%20of%20the%20field%2C%20including%20larger%20industry%20players%2C%20academic%20institutions%2C%20and%20non%5Cu2010English%20content.%22%2C%22date%22%3A%2208%5C%2F2024%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1002%5C%2Fohn.830%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Faao-hnsfjournals.onlinelibrary.wiley.com%5C%2Fdoi%5C%2F10.1002%5C%2Fohn.830%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%220194-5998%2C%201097-6817%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-07-20T18%3A03%3A09Z%22%7D%7D%5D%7D
Frontiers | Bridge2AI Voice: Voice Artificial Intelligence Symposium. (2026). https://www.frontiersin.org/books/Bridge2AI_Voice_Voice_Artificial_Intelligence_Symposium/12162
Jenkins, P. D., Bedrick, S., Karstens, L., Hersh, W., the Bridge2AI-Voice Consortium, & Dorr, D. A. (2026). From voice biomarkers to telemedicine screening: developing and evaluating a voice-based AI model for laryngeal lesion detection using the Bridge2AI-Voice dataset. Frontiers in Digital Health, 8. https://doi.org/10.3389/fdgth.2026.1846369
Ebraheem, M., Toghranegar, J., Bridge2AI-Voice Consortium, Bensoussan, Y., & Templeton, J. M. (2026). Explainable and Interpretable AI for Voice and Speech Analysis in Clinical Care: Systematic Review. Journal of Medical Internet Research, 28, e83790–e83790. https://doi.org/10.2196/83790
Elemento, O., Sigaras, A., Colonel, J. T., Hajirasouliha, I., Ghosh, S. S., Bensoussan, Y., Bridge2AI-Voice Consortium, & Rameau, A. (2026). Towards A Foundation Model for Clinical Voice Biomarkers. https://doi.org/10.64898/2026.05.28.26354346
Bélisle-Pipon, J.-C., Toghranegar, J., & Powell, M. E. (2026). Editorial: Advancing vocal biomarkers and voice AI in healthcare: multidisciplinary focus on responsible and effective development and use. Frontiers in Digital Health, 8, 1811486. https://doi.org/10.3389/fdgth.2026.1811486
Kutler, R. B., & Rameau, A. (2026). Artificial Intelligence in Voice Disorders: Current Landscape, Emerging Applications and Future Directions. World Journal of Otorhinolaryngology - Head and Neck Surgery, wjo2.70103. https://doi.org/10.1002/wjo2.70103
Salvi Cruz, S., Toghranegar, J., Malin, B., Mehra, T., MacDonald, B., Speights, M., Noufi, C., Fossat, Y., Fagherrazi, G., Cummins, N., Elbeji, A., Blatter, A., Gelbard, A., Arienzo, A., Baur, S., Wetstone, K., Peller, J., Au, R., Botha, H., … Bensoussan, Y. (2026). Translating AI research into reality: summary of the 2025 voice AI Symposium and Hackathon. Frontiers in Digital Health, 8, 1754426. https://doi.org/10.3389/fdgth.2026.1754426
Rahman, J. M. W., Boyer, M., Sanchez, V. A., & Bensoussan, Y. (2026). Why Hearing Health Must Be Part of Voice Biomarker Research. JAMA Otolaryngology–Head & Neck Surgery, 152(3), 225. https://doi.org/10.1001/jamaoto.2025.4836
Malo, M.-F., Bouhouita-Guermech, S., Gallois, H., Ravitsky, V., Bridge2AI Voice Consortium, & Bélisle-Pipon, J.-C. (2026). Using voice and speech data in healthcare: a scoping review of the ethical, legal and social implications. Frontiers in Digital Health, 8, 1750111. https://doi.org/10.3389/fdgth.2026.1750111
Lee, M., Meylan, S., Shobin, E., the SpeechDx Consortium, Nisenbaum, L., Sukumar, A., & Kourtis, L. (2026). Digital speech‐based markers to advance prognosis in Alzheimer’s disease. Alzheimer’s & Dementia, 22(6), e71489. https://doi.org/10.1002/alz.71489
He, L., Li, H., Wang, S., Baik, E., Kervin, S., Zhao, R., Ramos, J. M., Bridge2AI‐Voice Consortium, Colonel, J., & Rameau, A. (2026). Decoding Gender in Cough Sounds: A Transformer‐Based Analysis. The Laryngoscope, 136(6), 2519–2527. https://doi.org/10.1002/lary.70393
Piao, R., Lu, Y., Kemps, H., Xia, T., & Saeed, A. (2025). Unified Acoustic Representations for Screening Neurological and Respiratory Pathologies from Voice (arXiv:2508.20717). arXiv. https://doi.org/10.48550/arXiv.2508.20717
Pizzimenti, M., Kalia, A., Toghranegar, J. A., Ebraheem, M., Cummins, N., Ghosh, S. S., Anibal, J. T., Au, R., Azarang, A., Bahr, R. H., Bedrick, S. D., Botha, H., Coleman, O. C., Elbeji, A., Kourtis, L. C., Rameau, A., Sara, J. D. S., Watts, S. W., Hemmerling, D., … Fagherazzi, G. (2025). Consensus-Based Definitions for Vocal Biomarkers: The International VOCAL Initiative. medRxiv. https://doi.org/10.1101/2025.10.23.25338518
Miao, S., Choi, J., Russell, L., Bensoussan, Y., Ng, E., Johnson, A., Wolter, N. E., Propst, E. J., & Siu, J. M. (2025). Feasibility of a Pediatric Voice Protocol for Artificial Intelligence Research. Journal of Voice. https://doi.org/10.1016/j.jvoice.2025.10.010
Mahapatra, I., & Mahapatra, N. R. (2025, November 27). FAIR Voice Biomarker Data for Safe-Assured Embodied Health AI. Embodied and Safe-Assured Robotic Systems. https://openreview.net/forum?id=L3VxhW2KWh
Dorr, D. A., Krussel, A., Hauck, R., Jackson, C., Dalal, A., Bedrick, S., Payne, P. R. O., Bridge2AI-Voice Consortium, Hersh, W., Bensoussan, Y., Elemento, O., Rameau, A., Sigaras, A., Ghosh, S., Powell, M., Ravitsky, V., Christophe Belisle-Pipon, J., Dorr, D., Payne, P., … Goldenberg, A. (2025). Adapting data science competencies by role and purpose: Voice AI. Frontiers in Digital Health, 7. https://doi.org/10.3389/fdgth.2025.1610253
Gallois, H., Ivkovic, L., Evangelista, E., Bensoussan, Y., Dorr, D. A., Elemento, O., Ghosh, S. S., Johnson, A., Payne, P., Powell, M. E., Rameau, A., Ravitsky, V., Sigaras, A., Bélisle-Pipon, J.-C., & B2AI-Voice Consortium. (2025). “Low Risk, High Happiness”: A Review of Openly Declared Ethical and Legal Practices in Voice Biomarker Health-Tech Start-Ups. Health Care Analysis. https://doi.org/10.1007/s10728-025-00539-w
Caufield, H., Ghosh, S., Kong, S. W., Parker, J., Sheffield, N., Patel, B., Williams, A., Clark, T., & Munoz-Torres, M. C. (2025). Standards in the Preparation of Biomedical Research Metadata: A Bridge2AI Perspective (arXiv:2509.10432). arXiv. https://doi.org/10.48550/arXiv.2509.10432
Russell, L., Bensoussan, Y., Ng, E., Johnson, A., Miao, S., Wolter, N. E., Propst, E. J., & Siu, J. M. (2025). Developing age-specific protocols for pediatric voice databases in artificial intelligence research. International Journal of Pediatric Otorhinolaryngology, 196, 112455. https://doi.org/10.1016/j.ijporl.2025.112455
Piao, R., Lu, Y., Kemps, H., Xia, T., & Saeed, A. (2025). Unified Multi-task Learning for Voice-Based Detection of Diverse Clinical Conditions (arXiv:2508.20717). arXiv. https://doi.org/10.48550/arXiv.2508.20717
Nejat, P., Bachman, A. D., Stubbs, V. M., Duffy, J. R., Stricker, J. L., Herasevich, V., Jones, D. T., Utianski, R. L., & Botha, H. (2025). Who Makes It Through the Funnel? Sociodemographic Drivers of Recruitment Completion into an AI-Ready Digital Speech Bank. medRxiv, 2025.08.18.25333909. https://doi.org/10.1101/2025.08.18.25333909
Jenkins, P., Harrison, R., Bedrick, S., Karstens, L., Bridge2AI-Voice Consortium, Hersh, W., Bensoussan, Y., Elemento, O., Rameau, A., Sigaras, A., Ghosh, S., Powell, M., Ravitsky, V., Belisle-Pipon, J. C., Dorr, D., Payne, P., Johnson, A., Bahr, R., Bolser, D., … Goldenberg, A. (2025). Voice as a biomarker: exploratory analysis for benign and malignant vocal fold lesions. Frontiers in Digital Health, 7. https://doi.org/10.3389/fdgth.2025.1609811
Awan, S. N., Bensoussan, Y., Watts, S., Boyer, M., Budinsky, R., & Bahr, R. H. (2025). Influence of recording instrumentation on measurements of voice in sentence contexts: use of smartphones and tablets. Frontiers in Digital Health, 7. https://doi.org/10.3389/fdgth.2025.1610772
Kalia, A., Boyer, M., Fagherazzi, G., Bélisle-Pipon, J.-C., & Bensoussan, Y. (2025). Master protocols in vocal biomarker development to reduce variability and advance clinical precision: a narrative review. Frontiers in Digital Health, 7. https://doi.org/10.3389/fdgth.2025.1619183
Blatter, A., Gallois, H., Evangelista, E., Bensoussan, Y., Bridge2AI-Voice Consortium, & Bélisle-Pipon, J.-C. (2025). “Voice is the New Blood”: a discourse analysis of voice AI health-tech start-up websites. Frontiers in Digital Health, 7, 1568159. https://doi.org/10.3389/fdgth.2025.1568159
Anibal, J., Doctor, R., Boyer, M., Newberry, K., De Santiago, I., Awan, S., Abdel-Aty, Y., Dion, G., Daoud, V., Huth, H., Watts, S., Wood, B. J., Clifton, D., Gelbard, A., Powell, M., Toghranegar, J., & Bensoussan, Y. (2025). Transformers for rapid detection of airway stenosis and stridor. Scientific Reports, 15(1), 15394. https://doi.org/10.1038/s41598-025-99369-y
Moothedan, E., Boyer, M., Watts, S., Abdel-Aty, Y., Ghosh, S., Rameau, A., Sigaras, A., Elemento, O., Bridge2AI-Voice Consortium, & Bensoussan, Y. (2025). The Bridge2AI-voice application: initial feasibility study of voice data acquisition through mobile health. Frontiers in Digital Health, 7, 1514971. https://doi.org/10.3389/fdgth.2025.1514971
Díaz-Ocampo, E., Martínez-Tapia, A., Magadan-Salazar, A., Pinto Elías, R., Lopez, M., & Bensoussan, Y. (2025). Gender Recognition of Teen and Adult Voices in Non-Tonal and Tonal Languages in Uncontrolled Environments. Computación y Sistemas, 29. https://doi.org/10.13053/cys-29-1-4495
Bélisle-Pipon, J.-C., Anibal, J., Bahr, R., Bedrick, S., Coleman, O., Dorr, D., Evans, B. J., Fagherazzi, G., Gelbard, A., Ghosh, S., Ho, A., Jackson, C., Joachim, D., Kourtis, L., Krussel, A., Lahav, A., Leuze, B., MacDonald, B., Miller, G., … Bensoussan, Y. (2025). Interactive Panel Summaries of the 2024 Voice AI Symposium. Frontiers in Digital Health, 7, 1484521. https://doi.org/10.3389/fdgth.2025.1484521
Anibal, J., Huth, H., Li, M., Hazen, L., Daoud, V., Ebedes, D., Lam, Y. M., Nguyen, H., Hong, P. V., Kleinman, M., Ost, S., Jackson, C., Sprabery, L., Elangovan, C., Krishnaiah, B., Akst, L., Lina, I., Elyazar, I., Ekawati, L., … Wood, B. (2025). Voice EHR: introducing multimodal audio data for health. Frontiers in Digital Health, 6, 1448351. https://doi.org/10.3389/fdgth.2024.1448351
Rincon, J., Pelletier, A. R., Gilliland, D., Wang, W., Wang, D., Sankar, B. S., Scott-Sheldon, L., Gebreab, S., Hersh, W., Rashidi, P., Baxter, S., Schulz, W., Ideker, T., Bensoussan, Y., Boutros, P. C., Bui, A. A. T., Walsh, C., Watson, K. E., & Ping, P. (2025). Bridge2AI: Building A Cross-disciplinary Curriculum Towards AI-Enhanced Biomedical and Clinical Care. arXiv. https://doi.org/10.48550/ARXIV.2505.14757
Patel, R., Price, N., Bahr, R., Bedrick, S., Bensoussan, Y., Bélisle-Pipon, J.-C., Dorr, D., Jackson, C., Krussel, A., Salvi Cruz, S., Toghranegar, J., Watts, S., Zhao, R., The Bridge2AI-Voice Consortium, & Powell, M. (2024). Summary of Keynote Speeches from the 2024 Voice AI Symposium, presented by the Bridge2AI-Voice Consortium. Frontiers in Digital Health, 6, 1484503. https://doi.org/10.3389/fdgth.2024.1484503
Fagherazzi, G., & Bensoussan, Y. (2024). The Imperative of Voice Data Collection in Clinical Trials. Digital Biomarkers, 8(1), 207–209. https://doi.org/10.1159/000541456
Anibal, J., Gunkel, J., Awan, S., Huth, H., Nguyen, H., Le, T., Bélisle-Pipon, J.-C., Boyer, M., Hazen, L., Bensoussan, Y., Clifton, D., & Wood, B. (2024). The doctor will polygraph you now: ethical concerns with AI for fact-checking patients. ArXiv, arXiv:2408.07896v2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11468487/
Bahr, R., Anibal, J., Bedrick, S., Bélisle-Pipon, J.-C., Bensoussan, Y., Blaylock, N., Castermans, J., Comito, K., Dorr, D., Hale, G., Jackson, C., Krussel, A., Kuman, K., Komarlu, A. R., Lerner-Ellis, J., Powell, M., Ravitsky, V., Rameau, A., Reavis, C., … the Bridge2AI-Voice Consortium. (2024). Workshop summaries from the 2024 voice AI symposium, presented by the Bridge2AI-voice consortium. Frontiers in Digital Health, 6, 1484818. https://doi.org/10.3389/fdgth.2024.1484818
Evangelista, E., & Bensoussan, Y. (2024). Standardization, Collaboration, and Education in the Implementation of Artificial Intelligence in Otolaryngology: The Key to Scalable Impact. Otolaryngologic Clinics of North America, 57(5), 897–908. https://doi.org/10.1016/j.otc.2024.04.005
Awan, S. N., Bahr, R., Watts, S., Boyer, M., Budinsky, R., & Bensoussan, Y. (2024). Evidence-Based Recommendations for Tablet Recordings From the Bridge2AI-Voice Acoustic Experiments. Journal of Voice. https://doi.org/10.1016/j.jvoice.2024.08.029
Rameau, A., Ghosh, S., Sigaras, A., Elemento, O., Belisle-Pipon, J.-C., Ravitsky, V., Powell, M., Johnson, A., Dorr, D., Payne, P., Boyer, M., Watts, S., Bahr, R., Rudzicz, F., Lerner-Ellis, J., Awan, S., Bolser, D., & Bensoussan, Y. (2024). Developing Multi-Disorder Voice Protocols: A team science approach involving clinical expertise, bioethics, standards, and DEI. Interspeech 2024, 1445–1449. https://doi.org/10.21437/Interspeech.2024-1926
Gopinathan, M., Krol, O., Karstens, L., Bedrick, S., & Hersh, B. (2024, August 10). Voice as a Biomarker: Exploratory Analysis of Airway Stenosis [Poster Presentation]. Bridge2AI-Voice Summer School Hackathon.
Harrison, R., Jenkins, P., Karstens, L., Bedrick, S., & Hersh, B. (2024, August 10). Voice as a Biomarker: Exploratory Analysis for Benign and Malignant Vocal Fold Lesions [Poster Presentation].
Jang, D., Babatunde, A., & Lu, E. (2024, August 10). Preliminary Dataset Exploration of Hypertension Voice Biomarkers [Poster Presentation]. Bridge2AI-Voice Summer School Hackathon.
Kapoor, U., Chaitanya Nama, G. K., & Khorrami, P. (2024, August 10). Optimized Preprocessing Steps and Neural Network Parameters for Generalized Stridor Detection and Characterization [Poster Presentation]. Bridge2AI-Voice Summer School Hackathon.
Luu, M., & Olivio Cauberghs, E. (2024, August 10). Identifying Biomarkers of Unilateral Vocal Fold Paralysis for Artificial Intelligence & Machine Learning Development [Poster Presentation]. Bridge2AI-Voice Summer School Hackathon.
Margolis, H., Mathur, A., & Rashkovich, S. (2024, August 10). Disease Classification with Voice Biomarkers: Identifying Depression and Anxiety [Poster Presentation]. Bridge2AI-Voice Summer School Hackathon.
Power, W., & Kyeremateng, I. (2024, August 10). Depression Prediction using Machine Learning with Clinical and Audio Data from the Bridge2AI Voice Project [Poster Presentation]. Bridge2AI-Voice Summer School Hackathon.
Schimmelpfennig, L., Keshariya, A., & Abrams, Z. (2024, August 10). Airway Stenosis Classification With Breathing Audio Data [Poster Presentation]. Bridge2AI-Voice Summer School Hackathon.
Awan, S. N., Bahr, R., Watts, S., Boyer, M., Budinsky, R., Bridge2AI Voice Consortium, & Bensoussan, Y. (2024). Validity of Acoustic Measures Obtained Using Various Recording Methods Including Smartphones With and Without Headset Microphones. Journal of Speech, Language, and Hearing Research, 67(6), 1712–1730. https://doi.org/10.1044/2024_JSLHR-23-00759
Rogers, H. P., Hseu, A., Kim, J., Silberholz, E., Jo, S., Dorste, A., & Jenkins, K. (2024). Voice as a Biomarker of Pediatric Health: A Scoping Review. Children, 11(6), 684. https://doi.org/10.3390/children11060684
Bensoussan, Y., Elemento, O., & Rameau, A. (2024). Voice as an AI Biomarker of Health—Introducing Audiomics. JAMA Otolaryngology–Head & Neck Surgery, 150(4), 283–284. https://doi.org/10.1001/jamaoto.2023.4807
Evangelista, E. G., Bélisle‐Pipon, J., Naunheim, M. R., Powell, M., Gallois, H., Bridge2AI‐Voice Consortium, & Bensoussan, Y. (2024). Voice as a Biomarker in Health‐Tech: Mapping the Evolving Landscape of Voice Biomarkers in the Start‐Up World. Otolaryngology–Head and Neck Surgery, 171(2), 340–352. https://doi.org/10.1002/ohn.830