{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T14:05:56Z","timestamp":1782741956911,"version":"3.54.5"},"reference-count":58,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2025,7,28]],"date-time":"2025-07-28T00:00:00Z","timestamp":1753660800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: Accurate assessment of speech intelligibility is necessary for individuals with motor speech disorders. Transcription or scaled rating methods by na\u00efve listeners are the most reliable tasks for these purposes; however, they are often resource-intensive and time-consuming within clinical contexts. Automatic speech recognition (ASR) systems, which transcribe speech into text, have been increasingly utilized for assessing speech intelligibility. This study investigates the feasibility of using an open-source ASR system to assess speech intelligibility in Hebrew and English speakers with Down syndrome (DS). Methods: Recordings from 65 Hebrew- and English-speaking participants were included: 33 speakers with DS and 32 typically developing (TD) peers. Speech samples (words, sentences) were transcribed using Whisper (OpenAI) and by na\u00efve listeners. The proportion of agreement between ASR transcriptions and those of na\u00efve listeners was compared across speaker groups (TD, DS) and languages (Hebrew, English) for word-level data. Further comparisons for Hebrew speakers were conducted across speaker groups and stimuli (words, sentences). Results: The strength of the correlation between listener and ASR transcription scores varied across languages, and was higher for English (r = 0.98) than for Hebrew (r = 0.81) for speakers with DS. A higher proportion of listener\u2013ASR agreement was demonstrated for TD speakers, as compared to those with DS (0.94 vs. 0.74, respectively), and for English, in comparison to Hebrew speakers (0.91 for English DS speakers vs. 0.74 for Hebrew DS speakers). Listener\u2013ASR agreement for single words was consistently higher than for sentences among Hebrew speakers. Speakers\u2019 intelligibility influenced word-level agreement among Hebrew- but not English-speaking participants with DS. Conclusions: ASR performance for English closely approximated that of na\u00efve listeners, suggesting potential near-future clinical applicability within single-word intelligibility assessment. In contrast, a lower proportion of agreement between human listeners and ASR for Hebrew speech indicates that broader clinical implementation may require further training of ASR models in this language.<\/jats:p>","DOI":"10.3390\/diagnostics15151892","type":"journal-article","created":{"date-parts":[[2025,7,28]],"date-time":"2025-07-28T14:50:03Z","timestamp":1753714203000},"page":"1892","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Automated Assessment of Word- and Sentence-Level Speech Intelligibility in Developmental Motor Speech Disorders: A Cross-Linguistic Investigation"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6118-9201","authenticated-orcid":false,"given":"Micalle","family":"Carl","sequence":"first","affiliation":[{"name":"Department of Communication Disorders, Ariel University, Ariel 40700, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9228-309X","authenticated-orcid":false,"given":"Michal","family":"Icht","sequence":"additional","affiliation":[{"name":"Department of Communication Disorders, Ariel University, Ariel 40700, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1044\/1058-0360.0302.81","article-title":"The Intelligibility of Children\u2019s Speech: A Review of Evaluation Procedures","volume":"3","author":"Kent","year":"1994","journal-title":"Am. J. Speech Lang. Pathol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1111\/1460-6984.12061","article-title":"Measuring up to Speech Intelligibility","volume":"48","author":"Miller","year":"2013","journal-title":"Int. J. Lang. Commun. Disord."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1044\/2020_PERSP-19-00110","article-title":"Measuring Speech Intelligibility in Children with Motor Speech Disorders","volume":"5","author":"Allison","year":"2020","journal-title":"Perspect. ASHA Spec. Interest Groups"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3022","DOI":"10.1121\/1.1515793","article-title":"The Effects of Familiarization on Intelligibility and Lexical Segmentation in Hypokinetic and Ataxic Dysarthria","volume":"112","author":"Liss","year":"2002","journal-title":"J. Acoust. Soc. Am."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2128","DOI":"10.1044\/2022_JSLHR-21-00589","article-title":"Validity of Off-the-Shelf Automatic Speech Recognition for Assessing Speech Intelligibility and Speech Severity in Speakers with Amyotrophic Lateral Sclerosis","volume":"65","author":"Gutz","year":"2022","journal-title":"J. Speech Lang. Hear. Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"e40567","DOI":"10.2196\/40567","article-title":"Automatic Assessment of Intelligibility in Noise in Parkinson Disease: Validation Study","volume":"24","author":"Walsh","year":"2022","journal-title":"J. Med. Internet Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1186\/s13636-023-00318-2","article-title":"A Survey of Technologies for Automatic Dysarthric Speech Recognition","volume":"2023","author":"Qian","year":"2023","journal-title":"EURASIP J. Audio Speech Music Process."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1159\/000091735","article-title":"Estimating the Intelligibility of Speakers with Dysarthria","volume":"58","author":"Hustad","year":"2006","journal-title":"Folia Phoniatr. Logop."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1044\/1058-0360.0501.55","article-title":"Comprehensibility of Dysarthric Speech: Implications for Assessment and Treatment Planning","volume":"5","author":"Yorkston","year":"1996","journal-title":"Am. J. Speech Lang. Pathol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1055\/s-2007-986527","article-title":"Application of the ICF in Reduced Speech Intelligibility in Dysarthria","volume":"28","author":"Dykstra","year":"2007","journal-title":"Semin. Speech Lang."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1044\/1092-4388(2012\/12-0148)","article-title":"Speech Impairment in Down Syndrome: A Review","volume":"56","author":"Kent","year":"2013","journal-title":"J. Speech Lang. Hear. Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1044\/2017_AJSLP-17-0002","article-title":"Single-Word Speech Intelligibility in Children and Adults with Down Syndrome","volume":"27","author":"Wild","year":"2018","journal-title":"Am. J. Speech Lang. Pathol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1159\/000108337","article-title":"Effects of Speech Stimuli and Dysarthria Severity on Intelligibility Scores and Listener Confidence Ratings for Speakers with Cerebral Palsy","volume":"59","author":"Hustad","year":"2007","journal-title":"Folia Phoniatr. Logop."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3110","DOI":"10.1044\/2017_JSLHR-S-17-0127","article-title":"Generalized Adaptation to Dysarthric Speech","volume":"60","author":"Borrie","year":"2017","journal-title":"J. Speech Lang. Hear. Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"396","DOI":"10.3109\/17549507.2013.876667","article-title":"Impact of Sentence Length and Phonetic Complexity on Intelligibility of 5-Year-Old Children with Cerebral Palsy","volume":"16","author":"Allison","year":"2014","journal-title":"Int. J. Speech Lang. Pathol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1044\/2018_AJSLP-18-0049","article-title":"Shorter Sentence Length Maximizes Intelligibility and Speech Motor Performance in Persons with Dysarthria Due to Amyotrophic Lateral Sclerosis","volume":"28","author":"Allison","year":"2019","journal-title":"Am. J. Speech Lang. Pathol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"10","DOI":"10.3104\/reports.301","article-title":"Speech Intelligibility and Childhood Verbal Apraxia in Children with Down Syndrome","volume":"10","author":"Kumin","year":"2006","journal-title":"Syndr. Res. Pract."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"772","DOI":"10.1080\/02699206.2019.1595735","article-title":"Estimates of the Prevalence of Speech and Motor Speech Disorders in Adolescents with Down Syndrome","volume":"33","author":"Wilson","year":"2019","journal-title":"Clin. Linguist. Phon."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1044\/2024_AJSLP-24-00247","article-title":"Can We Trust Our Ears? How Accurate and Reliable Are Speech-Language Pathologists\u2019 Estimates of Children\u2019s Speech Intelligibility?","volume":"34","author":"Allison","year":"2025","journal-title":"Am. J. Speech Lang. Pathol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3100","DOI":"10.1044\/2022_JSLHR-22-00287","article-title":"Vowel Acoustics as Predictors of Speech Intelligibility in Dysarthria","volume":"66","author":"Thompson","year":"2023","journal-title":"J. Speech Lang. Hear. Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1080\/02699206.2021.2009918","article-title":"Assessing Speech Intelligibility of Pathological Speech: Test Types, Ratings and Transcription Measures","volume":"37","author":"Xue","year":"2023","journal-title":"Clin. Linguist. Phon."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"873","DOI":"10.1044\/2017_AJSLP-16-0112","article-title":"Speech-Language Pathologists\u2019 Use of Intelligibility Measures in Adults with Dysarthria","volume":"26","author":"Gurevich","year":"2017","journal-title":"Am. J. Speech Lang. Pathol."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Tobin, J., Tomanek, K., and Venugopalan, S. (2025, January 6). Towards a Single ASR Model That Generalizes to Disordered Speech. Proceedings of the ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hyderabad, India.","DOI":"10.1109\/ICASSP49660.2025.10888895"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3004","DOI":"10.1044\/2024_JSLHR-24-00009","article-title":"Accuracy of Speech Sound Analysis: Comparison of an Automatic Artificial Intelligence Algorithm with Clinician Assessment","volume":"67","author":"Carl","year":"2024","journal-title":"J. Speech Lang. Hear. Res."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3433607","article-title":"A Longitudinal Evaluation of Tablet-Based Child Speech Therapy with Apraxia World","volume":"14","author":"Hair","year":"2021","journal-title":"ACM Trans. Access. Comput."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2964","DOI":"10.1044\/2024_JSLHR-24-00049","article-title":"Automatic Speech Recognition in Primary Progressive Apraxia of Speech","volume":"67","author":"Tetzloff","year":"2024","journal-title":"J. Speech Lang. Hear. Res."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"MacDonald, R.L., Jiang, P.-P., Cattiau, J., Heywood, R., Cave, R., Seaver, K., Ladewig, M.A., Tobin, J., Brenner, M.P., and Nelson, P.C. (2021, January 30). Disordered Speech Data Collection: Lessons Learned at 1 Million Utterances from Project Euphonia. Proceedings of the Interspeech 2021, Brno, Czechia.","DOI":"10.21437\/Interspeech.2021-697"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1044\/2024_JSLHR-23-00740","article-title":"Speech Technology for Automatic Recognition and Assessment of Dysarthric Speech: An Overview","volume":"68","author":"Bhat","year":"2025","journal-title":"J. Speech Lang. Hear. Res."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3020","DOI":"10.1007\/s00034-023-02592-z","article-title":"Enhancing Children\u2019s Short Utterance-Based ASV Using Inverse Gamma-Tone Filtered Cepstral Coefficients","volume":"43","author":"Aziz","year":"2024","journal-title":"Circuits Syst. Signal Process."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"4186","DOI":"10.1044\/2024_JSLHR-24-00097","article-title":"How People Living with Amyotrophic Lateral Sclerosis Use Personalized Automatic Speech Recognition Technology to Support Communication","volume":"67","author":"Cave","year":"2024","journal-title":"J. Speech Lang. Hear. Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"4176","DOI":"10.1044\/2024_JSLHR-24-00045","article-title":"Automatic Speech Recognition of Conversational Speech in Individuals with Disordered Speech","volume":"67","author":"Tobin","year":"2024","journal-title":"J. Speech Lang. Hear. Res."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.specom.2023.02.004","article-title":"Measuring the Intelligibility of Dysarthric Speech through Automatic Speech Recognition in a Pluricentric Language","volume":"148","author":"Xue","year":"2023","journal-title":"Speech Commun."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Tr\u00f6ger, J., D\u00f6rr, F., Schwed, L., Linz, N., K\u00f6nig, A., Thies, T., Barbe, M.T., Orozco-Arroyave, J.R., and Rusz, J. (2024). An Automatic Measure for Speech Intelligibility in Dysarthrias\u2014Validation across Multiple Languages and Neurological Disorders. Front. Digit. Health, 6.","DOI":"10.3389\/fdgth.2024.1440986"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Artale, A., Cortellessa, G., and Montali, M. (2024, January 25\u201328). ASR Systems Under Acoustic Challenges: A Multilingual Study. Proceedings of the AIxIA 2024\u2014Advances in Artificial Intelligence, Bolzano, Italy.","DOI":"10.1007\/978-3-031-80607-0"},{"key":"ref_35","unstructured":"Hsu, M.-H., Huang, K.P., and Lee, H. (2024). Meta-Whisper: Speech-Based Meta-ICL for ASR on Low-Resource Languages. arXiv."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Huang, S.-S., Huang, K.-P., Liu, A.T., and Lee, H.-Y. (2025, January 6). Enhancing Multilingual ASR for Unseen Languages via Language Embedding Modeling. Proceedings of the ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hyderabad, India.","DOI":"10.1109\/ICASSP49660.2025.10890363"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Turetzky, A., Tal, O., Segal-Feldman, Y., Dissen, Y., Zeldes, E., Roth, A., Cohen, E., Shrem, Y., Chernyak, B.R., and Seleznova, O. (2024). HebDB: A Weakly Supervised Dataset for Hebrew Speech Processing. arXiv.","DOI":"10.21437\/Interspeech.2024-417"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"025206","DOI":"10.1121\/10.0024876","article-title":"Evaluating OpenAI\u2019s Whisper ASR: Performance Analysis across Diverse Accents and Speaker Traits","volume":"4","author":"Graham","year":"2024","journal-title":"JASA Express Lett."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Rowe, H.P., Gutz, S.E., Maffei, M.F., Tomanek, K., and Green, J.R. (2022). Characterizing Dysarthria Diversity for Automatic Speech Recognition: A Tutorial From the Clinical Perspective. Front. Comput. Sci., 4.","DOI":"10.3389\/fcomp.2022.770210"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"483","DOI":"10.3109\/17549507.2015.1112836","article-title":"Motor Speech Skills in Children with Down Syndrome: A Descriptive Study","volume":"18","author":"Rupela","year":"2016","journal-title":"Int. J. Speech Lang. Pathol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1080\/02699200050024001","article-title":"John Acoustic Variability in Dysarthria and Computer Speech Recognition","volume":"14","author":"Wilson","year":"2000","journal-title":"Clin. Linguist. Phon."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1044\/2019_JSLHR-19-00204","article-title":"Vowel Acoustics and Speech Intelligibility in Young Adults with down Syndrome","volume":"63","author":"Carl","year":"2020","journal-title":"J. Speech Lang. Hear. Res."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"106529","DOI":"10.1016\/j.jcomdis.2025.106529","article-title":"Perceptual and Acoustic Predictors of Speech Intelligibility among Hebrew-Speaking Young Adults with down Syndrome","volume":"115","author":"Carl","year":"2025","journal-title":"J. Commun. Disord."},{"key":"ref_44","unstructured":"Rosin, D., and Yakir, P. (2000). Pictures for Examining Articulation and Naming of Hebrew-Speaking Children in Israel."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1044\/2018_AJSLP-17-0131","article-title":"Stealing Cookies in the Twenty-First Century: Measures of Spoken Narrative in Healthy Versus Speakers with Aphasia","volume":"28","author":"Berube","year":"2019","journal-title":"Am. J. Speech Lang. Pathol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1111\/1460-6984.12737","article-title":"Validation and Cross-linguistic Adaptation of the Frenchay Dysarthria Assessment (FDA-2) Speech Intelligibility Tests: Hebrew Version","volume":"57","author":"Icht","year":"2022","journal-title":"Int. J. Lang. Commun. Disord."},{"key":"ref_47","unstructured":"Hodge, M., Daniels, J., and Gotzke, C.L. (2009). TOCS+ Intelligibility Measures (Version 5.3) [Computer Software], University of Alberta."},{"key":"ref_48","first-page":"61","article-title":"Stability of Intelligibility Measures for Children with Dysarthria and Cerebral Palsy","volume":"18","author":"Hodge","year":"2010","journal-title":"J. Med. Speech-Lang. Pathol."},{"key":"ref_49","unstructured":"Radford, A., Kim, J.W., Xu, T., Brockman, G., McLeavey, C., and Sutskever, I. (2023, January 23\u201329). Robust Speech Recognition via Large-Scale Weak Supervision. Proceedings of the International Conference on Machine Learning, Honolulu, HI, USA."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"388","DOI":"10.3758\/s13428-019-01237-x","article-title":"Gorilla in Our Midst: An Online Behavioral Experiment Builder","volume":"52","author":"Flitton","year":"2020","journal-title":"Behav. Res. Methods"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"025204","DOI":"10.1121\/10.0024877","article-title":"Automatic Recognition of Second Language Speech-in-Noise","volume":"4","author":"Kim","year":"2024","journal-title":"JASA Express Lett."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"ooae130","DOI":"10.1093\/jamiaopen\/ooae130","article-title":"Decoding Disparities: Evaluating Automatic Speech Recognition System Performance in Transcribing Black and White Patient Verbal Communication with Nurses in Home Healthcare","volume":"7","author":"Zolnoori","year":"2024","journal-title":"JAMIA Open"},{"key":"ref_53","unstructured":"R Core Team (2020). R: A Language and Environment for Statistical Computing, R Core Team."},{"key":"ref_54","unstructured":"Lenth, R. (2025, July 24). Emmeans: Estimated Marginal Means, Aka Least-Squares Means. R Package Version 14301. Available online: https:\/\/CRAN.R-project.org\/package=emmeans."},{"key":"ref_55","first-page":"65","article-title":"A Simple Sequentially Rejective Multiple Test Procedure","volume":"6","author":"Holm","year":"1979","journal-title":"Scand. J. Stat."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"397","DOI":"10.21449\/ijate.1101295","article-title":"Comparison of Normality Tests in Terms of Sample Sizes under Different Skewness and Kurtosis Coefficients","volume":"9","author":"Demir","year":"2022","journal-title":"Int. J. Assess. Tools Educ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"106301","DOI":"10.1016\/j.jcomdis.2023.106301","article-title":"Assessing Speech Intelligibility of Pathological Speech in Sentences and Word Lists: The Contribution of Phoneme-Level Measures","volume":"102","author":"Xue","year":"2023","journal-title":"J. Commun. Disord."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Tobin, J., and Tomanek, K. (2022, January 23). Personalized Automatic Speech Recognition Trained on Small Disordered Speech Datasets. Proceedings of the ICASSP 2022\u20132022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Singapore.","DOI":"10.1109\/ICASSP43922.2022.9747516"}],"container-title":["Diagnostics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-4418\/15\/15\/1892\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:17:32Z","timestamp":1760033852000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-4418\/15\/15\/1892"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,28]]},"references-count":58,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2025,8]]}},"alternative-id":["diagnostics15151892"],"URL":"https:\/\/doi.org\/10.3390\/diagnostics15151892","relation":{},"ISSN":["2075-4418"],"issn-type":[{"value":"2075-4418","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,28]]}}}