{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T17:54:14Z","timestamp":1782928454253,"version":"3.54.5"},"reference-count":52,"publisher":"Public Library of Science (PLoS)","issue":"7","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100019771","name":"FP7 Coordination of Research Activities","doi-asserted-by":"publisher","award":["602245"],"award-info":[{"award-number":["602245"]}],"id":[{"id":"10.13039\/100019771","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NeurATRIS","award":["ANR-11-INBS-0011"],"award-info":[{"award-number":["ANR-11-INBS-0011"]}]},{"DOI":"10.13039\/501100001665","name":"Agence Nationale de la Recherche","doi-asserted-by":"publisher","award":["ANR-17-EURE-0017"],"award-info":[{"award-number":["ANR-17-EURE-0017"]}],"id":[{"id":"10.13039\/501100001665","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Agence Nationale pour la Recherche","award":["ANR-10-IDEX-0001-02 PSL"],"award-info":[{"award-number":["ANR-10-IDEX-0001-02 PSL"]}]},{"name":"Agence Nationale pour la Recherche","award":["ANR-19-P3IA-0001"],"award-info":[{"award-number":["ANR-19-P3IA-0001"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:p>Huntington\u2019s disease (HD) causes progressive disability through motor, psychiatric, and cognitive symptoms. Machine learning speech analysis can detect motor and cognitive symptoms of HD, but not yet psychiatric symptoms. This study investigated whether speech analyses can detect the presence of psychiatric symptoms in HD. Audio recordings of six narrative tasks (cookie-theft picture description, red-riding hood storytelling, most recent 24 hours recalling, happy, sad, or angry storytelling) were prospectively collected from subsequent genetically confirmed HD participants from the BIOHD and REPAIR CAPIT-HD-Beta cohorts at the Hospital Henri-Mondor, Cr\u00e9teil. Speech therapists blindly annotated speech samples to allow extraction of three types of features: linguistic, LASER, and acoustic features. Psychiatric symptoms in participants were detected using the Problem Behaviors Assessment Short version (PBA-s). Machine learning classifier models were trained on 80% of the 89 participants before being tested on the remaining 20% of individuals. F1-scores were calculated and compared to chance. Linguistic features detected obsessive\/compulsive behavior (OCB) with all but joy task, and best with the cookie task (F1-score: 0.67, confidence interval [0.47\u20130.86] (p\u2009\u2266\u20090.001)). They also best detected depression with the red-riding hood (F1 score 0.66, [0.45\u20130.87], p\u2009\u2266\u20090.001), apathy with the joy task (0.60, [0.39\u20130.81], p\u2009\u2266\u20090.001), but not irritability. LASER features best detected OCB (0.65, [0.45\u20130.84], p\u2009\u2266\u20090.001), depression (0.60, [0.40, 0.80], p\u2009\u2266\u20090.01) and apathy (0.61, [0.37, 0.86], p\u2009\u2266\u20090.001) from the red-riding hood task, but not irritability. Acoustic features best detected depression (0.63, [0.46, 0.80], p\u2009\u2266\u20090.001) and OCB (0.60, [0.43, 0.77], p\u2009\u2266\u20090.001) but not apathy nor irritability. This study showed that speech analyses can detect obsessive\/compulsive behaviors, depression, and apathy in HD participants but not irritability. Linguistic and LASER features provided the most consistent detections, but acoustic features also detected depression and OCB, highlighting their complementary role for psychiatric characterization in HD.<\/jats:p>","DOI":"10.1371\/journal.pone.0350118","type":"journal-article","created":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T17:21:30Z","timestamp":1782926490000},"page":"e0350118","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Development and validation of a machine learning model to detect psychiatric symptoms in Huntington\u2019s disease using speech analysis"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9945-3031","authenticated-orcid":true,"given":"Quang Tuan 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Perez","year":"2021"},{"key":"pone.0350118.ref020","doi-asserted-by":"crossref","first-page":"1310548","DOI":"10.3389\/fneur.2024.1310548","article-title":"Digital assessment of speech in Huntington disease","volume":"15","author":"AS Nunes","year":"2024","journal-title":"Front Neurol"},{"key":"pone.0350118.ref021","first-page":"1","author":"KC Fraser","year":"2016"},{"key":"pone.0350118.ref022","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.specom.2022.09.001","article-title":"Depression assessment in people with Parkinson\u2019s disease: the combination of acoustic features and natural language processing","volume":"145","author":"PA P\u00e9rez-Toro","year":"2022","journal-title":"Speech Communication"},{"key":"pone.0350118.ref023","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.cortex.2022.05.024","article-title":"Emotion expression through spoken language in Huntington disease","volume":"155","author":"C Gallezot","year":"2022","journal-title":"Cortex"},{"issue":"2","key":"pone.0350118.ref024","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1109\/TAFFC.2015.2457417","article-title":"The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for voice research and affective computing","volume":"7","author":"F Eyben","year":"2016","journal-title":"IEEE Trans Affective Comput"},{"issue":"1","key":"pone.0350118.ref025","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1212\/WNL.29.1.1","article-title":"Huntington disease: clinical care and evaluation","volume":"29","author":"I Shoulson","year":"1979","journal-title":"Neurology"},{"issue":"9","key":"pone.0350118.ref026","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1016\/S1474-4422(09)70170-X","article-title":"Biological and clinical manifestations of Huntington\u2019s disease in the longitudinal TRACK-HD study: cross-sectional analysis of baseline data","volume":"8","author":"SJ Tabrizi","year":"2009","journal-title":"Lancet Neurol"},{"issue":"5","key":"pone.0350118.ref027","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1002\/ana.410410521","article-title":"CAG repeat number governs the development rate of pathology in Huntington\u2019s disease","volume":"41","author":"JB Penney Jr","year":"1997","journal-title":"Ann Neurol"},{"issue":"24","key":"pone.0350118.ref028","doi-asserted-by":"crossref","first-page":"2495","DOI":"10.1212\/WNL.0000000000004743","article-title":"Motor, cognitive, and functional declines contribute to a single progressive factor in early HD","volume":"89","author":"SA Schobel","year":"2017","journal-title":"Neurology"},{"issue":"7","key":"pone.0350118.ref029","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1016\/S1474-4422(22)00120-X","article-title":"A biological classification of Huntington\u2019s disease: the Integrated Staging System","volume":"21","author":"SJ Tabrizi","year":"2022","journal-title":"Lancet Neurol"},{"key":"pone.0350118.ref030","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.parkreldis.2016.02.008","article-title":"Neuropsychiatric symptoms are very common in premanifest and early stage Huntington\u2019s Disease","volume":"25","author":"S Martinez-Horta","year":"2016","journal-title":"Parkinsonism Relat Disord"},{"issue":"4","key":"pone.0350118.ref031","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1016\/j.cpr.2007.10.001","article-title":"A meta-analysis of emotional reactivity in major depressive disorder","volume":"28","author":"LM Bylsma","year":"2008","journal-title":"Clin Psychol Rev"},{"key":"pone.0350118.ref032","first-page":"847","author":"S Scherer","year":"2013"},{"key":"pone.0350118.ref033","first-page":"7547","author":"S Alghowinem","year":"2013"},{"key":"pone.0350118.ref034","unstructured":"Boersma P, van Heuven V. Speak and unSpeak with PRAAT. 2001;5."},{"key":"pone.0350118.ref035","unstructured":"Titeux H, Riad R, Cao XN, Hamilakis N, Madden K, Cristia A. Seshat: a tool for managing and verifying annotation campaigns of audio data."},{"key":"pone.0350118.ref036","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1162\/tacl_a_00288","article-title":"Massively multilingual sentence embeddings for zero-shot cross-lingual transfer and beyond","volume":"7","author":"M Artetxe","year":"2019","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"pone.0350118.ref037","first-page":"1373","author":"M Honnibal","year":"2015"},{"key":"pone.0350118.ref038","unstructured":"Liu H, Xu C, Liang J. Dependency distance: a new perspective on syntactic patterns in natural languages. 57."},{"key":"pone.0350118.ref039","author":"R Speer","year":"2022","journal-title":"Rspeer\/wordfreq: v3.0"},{"issue":"3","key":"pone.0350118.ref040","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1007\/s10579-016-9364-5","article-title":"FEEL: a French Expanded Emotion Lexicon","volume":"51","author":"A Abdaoui","year":"2016","journal-title":"Lang Resources & Evaluation"},{"key":"pone.0350118.ref041","article-title":"Scikit-learn: Machine Learning in Python","author":"F Pedregosa","journal-title":"Machine Learning in Python"},{"issue":"5","key":"pone.0350118.ref042","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1001\/jamapsychiatry.2019.3671","article-title":"Establishment of best practices for evidence for prediction: a review","volume":"77","author":"RA Poldrack","year":"2020","journal-title":"JAMA Psychiatry"},{"key":"pone.0350118.ref043","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12916-014-0241-z","article-title":"Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement","volume":"13","author":"GS Collins","year":"2015","journal-title":"BMC Med"},{"issue":"2","key":"pone.0350118.ref044","doi-asserted-by":"crossref","first-page":"152","DOI":"10.2174\/1871527320666211213125847","article-title":"Speech as a biomarker for depression","volume":"22","author":"S Koops","year":"2023","journal-title":"CNS Neurol Disord Drug Targets"},{"issue":"1","key":"pone.0350118.ref045","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/j.neubiorev.2011.06.002","article-title":"Emotion recognition in Huntington\u2019s disease: a systematic review","volume":"36","author":"SMD Henley","year":"2012","journal-title":"Neurosci Biobehav Rev"},{"issue":"12","key":"pone.0350118.ref046","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.1007\/s00702-014-1229-8","article-title":"Characteristics and occurrence of speech impairment in Huntington\u2019s disease: possible influence of antipsychotic medication","volume":"121","author":"J Rusz","year":"2014","journal-title":"J Neural Transm (Vienna)"},{"key":"pone.0350118.ref047","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1016\/j.jpsychires.2023.03.035","article-title":"Speech graph analysis in obsessive-compulsive disorder: the relevance of dream reports","volume":"161","author":"M Gomes","year":"2023","journal-title":"J Psychiatr Res"},{"issue":"10","key":"pone.0350118.ref048","article-title":"Associations between the severity of obsessive-compulsive disorder and vocal features in children and adolescents: protocol for a statistical and machine learning analysis","volume":"11","author":"LKH Clemmensen","year":"2022","journal-title":"JMIR Res Protoc"},{"key":"pone.0350118.ref049","doi-asserted-by":"crossref","first-page":"1633492","DOI":"10.3389\/fpsyt.2025.1633492","article-title":"Emotional speech markers of psychiatric disturbance in Huntington\u2019s disease","volume":"16","author":"L Chenain","year":"2025","journal-title":"Front Psychiatry"},{"key":"pone.0350118.ref050","unstructured":"Chenain L, Bachoud-L\u00e9vi A, Clavel C. Acoustic characterization of Huntington\u2019s disease emotional expression: an explainable AI approach."},{"key":"pone.0350118.ref051","doi-asserted-by":"crossref","first-page":"1265880","DOI":"10.3389\/fpsyt.2023.1265880","article-title":"Automated analysis of speech as a marker of sub-clinical psychotic experiences","volume":"14","author":"J Olah","year":"2024","journal-title":"Front Psychiatry"},{"key":"pone.0350118.ref052","unstructured":"Abdallah-Qasaimeh B, Ratt\u00e9 S. 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