{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T05:44:38Z","timestamp":1777527878907,"version":"3.51.4"},"reference-count":75,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2021,10,25]],"date-time":"2021-10-25T00:00:00Z","timestamp":1635120000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100008982","name":"Qatar National Research Fund","doi-asserted-by":"publisher","award":["8-293-2-124"],"award-info":[{"award-number":["8-293-2-124"]}],"id":[{"id":"10.13039\/100008982","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Brain Sciences"],"abstract":"<jats:p>Childhood apraxia of speech (CAS) commonly affects the production of lexical stress contrast in polysyllabic words. Automated classification tools have the potential to increase reliability and efficiency in measuring lexical stress. Here, factors affecting the accuracy of a custom-built deep neural network (DNN)-based classification tool are evaluated. Sixteen children with typical development (TD) and 26 with CAS produced 50 polysyllabic words. Words with strong\u2013weak (SW, e.g., dinosaur) or WS (e.g., banana) stress were fed to the classification tool, and the accuracy measured (a) against expert judgment, (b) for speaker group, and (c) with\/without prior knowledge of phonemic errors in the sample. The influence of segmental features and participant factors on tool accuracy was analysed. Linear mixed modelling showed significant interaction between group and stress type, surviving adjustment for age and CAS severity. For TD, agreement for SW and WS words was &gt;80%, but CAS speech was higher for SW (&gt;80%) than WS (~60%). Prior knowledge of segmental errors conferred no clear advantage. Automatic lexical stress classification shows promise for identifying errors in children\u2019s speech at diagnosis or with treatment-related change, but accuracy for WS words in apraxic speech needs improvement. Further training of algorithms using larger sets of labelled data containing impaired speech and WS words may increase accuracy.<\/jats:p>","DOI":"10.3390\/brainsci11111408","type":"journal-article","created":{"date-parts":[[2021,10,25]],"date-time":"2021-10-25T21:40:21Z","timestamp":1635198021000},"page":"1408","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["An Automated Lexical Stress Classification Tool for Assessing Dysprosody in Childhood Apraxia of Speech"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5747-0888","authenticated-orcid":false,"given":"Jacqueline","family":"McKechnie","sequence":"first","affiliation":[{"name":"Faculty of Health Sciences, The University of Sydney, Camperdown, NSW 2006, Australia"},{"name":"Faculty of Health, University of Canberra, Bruce, ACT 2617, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1091-8531","authenticated-orcid":false,"given":"Mostafa","family":"Shahin","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, University of New South Wales, Sydney, NSW 2052, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Beena","family":"Ahmed","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, University of New South Wales, Sydney, NSW 2052, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5182-1007","authenticated-orcid":false,"given":"Patricia","family":"McCabe","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, The University of Sydney, Camperdown, NSW 2006, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joanne","family":"Arciuli","sequence":"additional","affiliation":[{"name":"College of Nursing and Health Sciences, Flinders University, Adelaide, SA 5042, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kirrie J.","family":"Ballard","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, The University of Sydney, Camperdown, NSW 2006, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,25]]},"reference":[{"key":"ref_1","unstructured":"American Speech-Language-Hearing Association (2012, March 08). 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