{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T09:01:47Z","timestamp":1790845307159,"version":"4.1.0"},"reference-count":66,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2024,6,17]],"date-time":"2024-06-17T00:00:00Z","timestamp":1718582400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Intl J Lang &amp;amp; Comm Disor"],"published-print":{"date-parts":[[2024,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Sustained vowels are important vocal tasks that have been investigated in discriminating voice disorders using acoustic analysis. To date, no study has combined vowel acoustic measures only that evaluate major aspects of the pathological voice signals in voice disorder discrimination.<\/jats:p><\/jats:sec><jats:sec><jats:title>Aims<\/jats:title><jats:p>To investigate the value of vowel acoustic measures that quantify glottal noise, signal stability, signal periodicity, spectral slope and overall voice quality in discriminating female speakers with and without voice disorders.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods &amp; Procedures<\/jats:title><jats:p>Sustained vowel \/\u0251\/ samples were extracted from 133 voice\u2010disordered female patients and 97 non\u2010voice disordered female speakers and were signal typed prior to analysis. <jats:italic>Praat<\/jats:italic> software was used to measure harmonics\u2010to\u2010noise ratio (HNR), glottal\u2010to\u2010noise excitation ratio (GNE), the standard deviation of fundamental frequency (F0SD) and cepstral peak prominence (CPPp); and the <jats:italic>Analysis of Dysphonia in Speech and Voice<\/jats:italic> (ADSV) program was used to measure CPPadsv, low\/high spectral ratio (LH) and the cepstral\/spectral index of dysphonia (CSID). Outcome measures included sensitivity, specificity, and discrimination accuracy.<\/jats:p><\/jats:sec><jats:sec><jats:title>Outcomes &amp; Results<\/jats:title><jats:p>As individual acoustic measures, only spectral\u2010based measures showed good (CPPadsv) and acceptable (CSID) discrimination results. The HNR, GNE and CPPp measures had acceptable sensitivity but poor or non\u2010acceptable specificity and discrimination accuracy. Logistic regression models with all <jats:italic>Praat<\/jats:italic> measures (F0SD, HNR, GNE, CPPp) plus ADSV measures (CPPadsv, LH or CSID) provided excellent sensitivity, good\u2010to\u2010excellent specificity and excellent discrimination accuracy. ROC analysis for all individual measures showed that CPPadsv, CSID, CPPp, GNE and F0SD had the highest area under the curve (AUC) values.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions &amp; Implications<\/jats:title><jats:p>A combination of acoustic measures that evaluate the major aspects of vocal dysfunction resulted in good to excellent voice discrimination outcomes. Individual acoustic measures had lower discrimination ability than combined measures. The findings implied that acoustic measures extracted from a prolonged vowel were useful in voice disorder discrimination.<\/jats:p><\/jats:sec><jats:sec><jats:title>WHAT THIS PAPER ADDS<\/jats:title><jats:sec><jats:title>What is already known on this subject<\/jats:title><jats:p><jats:list list-type=\"bullet\">\n<jats:list-item><jats:p>Acoustic measures hold great value in discriminating voice disorders from normal voices. However, no study has evaluated discrimination values of a combination of sustained vowel acoustic measures that quantify additive noise, signal stability, signal periodicity, spectral slope and overall voice quality in single\u2010gender cohorts. Previous studies have not used signal typing (the classification of the acoustic signals) for time\u2010based measures, impacting the reliability of discrimination.<\/jats:p><\/jats:list-item><\/jats:list><\/jats:p><\/jats:sec><jats:sec><jats:title>What this study adds to the existing knowledge<\/jats:title><jats:p><jats:list list-type=\"bullet\">\n<jats:list-item><jats:p>This study was the first to implement signal typing to include sustained vowel samples of Types 1 and 2 signals for discrimination statistics. We showed that a combination of vocal acoustic measures using time\u2010 and spectral\u2010based extraction from the sustained \/\u0251\/ vowel evaluating additive noise, signal stability, signal periodicity, spectral slope and overall voice quality resulted in good to excellent sensitivity, specificity and discrimination accuracy. As individual measures, traditional time\u2010based measures such as HNR had rather limited discrimination values whilst spectral\u2010based measures provided higher discrimination values. Measures that are sensitive to signal types have low discrimination ability.<\/jats:p><\/jats:list-item><\/jats:list><\/jats:p><\/jats:sec><jats:sec><jats:title>What are the potential or actual clinical implications of this work?<\/jats:title><jats:p><jats:list list-type=\"bullet\">\n<jats:list-item><jats:p>The sustained vowel \/\u0251\/ is a relevant, universal vocal task for clinical application using acoustic measures to discriminate female speakers with and without voice disorders if signal typing is implemented. Clinical voice assessment using vowels may not be effective if relying solely on time\u2010based measurements. Spectral\u2010based measures perform better in voice disorder discrimination given their insensitivity to signal types. The most effective voice disorder discrimination could only be obtained using a combination of acoustic measures that quantify major phenomena in the signals of disordered voices. Using measures extracted from both programs, <jats:italic>Praat<\/jats:italic> and ADSV, is useful given that specific settings in a program may impact on discrimination accuracy.<\/jats:p><\/jats:list-item><\/jats:list><\/jats:p><\/jats:sec><\/jats:sec>","DOI":"10.1111\/1460-6984.13081","type":"journal-article","created":{"date-parts":[[2024,6,17]],"date-time":"2024-06-17T13:39:37Z","timestamp":1718631577000},"page":"2087-2102","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Voice disorder discrimination using vowel acoustic measures in female speakers"],"prefix":"10.1111","volume":"59","author":[{"given":"Duy Duong","family":"Nguyen","sequence":"first","affiliation":[{"name":"Voice Research Laboratory, Sydney School of Health Sciences, Faculty of Medicine and Health The University of Sydney  Sydney NSW Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3839-1353","authenticated-orcid":false,"given":"Daniel","family":"Novakovic","sequence":"additional","affiliation":[{"name":"Voice Research Laboratory, Sydney School of Health Sciences, Faculty of Medicine and Health The University of Sydney  Sydney NSW Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catherine","family":"Madill","sequence":"additional","affiliation":[{"name":"Voice Research Laboratory, Sydney School of Health Sciences, Faculty of Medicine and Health The University of Sydney  Sydney NSW Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,6,17]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvoice.2011.12.001"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.3109\/02699206.2010.492446"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvoice.2015.04.009"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1177\/000348941312200108"},{"key":"e_1_2_9_6_1","volume-title":"Clinical measurement of speech and voice","author":"Baken R.J.","year":"2000"},{"key":"e_1_2_9_7_1","first-page":"97","article-title":"Accurate short\u2010term analysis of the fundamental frequency and the harmonics\u2010to\u2010noise ratio of a sampled sound","volume":"17","author":"Boersma P.","year":"1993","journal-title":"IFA Proceedings"},{"key":"e_1_2_9_8_1","unstructured":"Boersma P.&Weenink D.(2023)Praat: doing phonetics by computer [Computer program][Online]. 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