{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T20:20:41Z","timestamp":1780777241293,"version":"3.54.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643682846","type":"print"},{"value":"9781643682853","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T00:00:00Z","timestamp":1653436800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,25]]},"abstract":"<jats:p>This paper presents a Support-Vector Machine (SVM) based method of classification of cross-correlated phoneme segments as part of the development of an automated Speech Sound Disorder (SSD) Screening tool. The pre-processing stage of the algorithm uses cross-correlation to segment the target phoneme and extracts data from the new homogeneously trimmed audio samples. Such data is then fed into the SVM-based classification script which currently achieves an accuracy of 97.5% on a dataset of 132 rows. Given the global context of an increasing trend in the incidence of Speech Sound Disorders (SSDs) amongst early-school aged children (5\u20136 years old), the constraints imposed by the new Corona virus pandemic, and the (consequent) shortage of professionally trained specialists, an automated screening tool would be of much assistance to Speech-Language Pathologists (SLPs).<\/jats:p>","DOI":"10.3233\/shti220500","type":"book-chapter","created":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T12:14:47Z","timestamp":1653480887000},"source":"Crossref","is-referenced-by-count":1,"title":["Support-Vector Machine-Based Classifier of Cross-Correlated Phoneme Segments for Speech Sound Disorder Screening"],"prefix":"10.3233","author":[{"given":"Emilian-Erman","family":"Mahmut","sequence":"first","affiliation":[{"name":"Department of Automation and Applied Informatics, Politehnica University Timisoara, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stelian","family":"Nicola","sequence":"additional","affiliation":[{"name":"Department of Automation and Applied Informatics, Politehnica University Timisoara, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vasile","family":"Stoicu-Tivadar","sequence":"additional","affiliation":[{"name":"Department of Automation and Applied Informatics, Politehnica University Timisoara, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Challenges of Trustable AI and Added-Value on Health"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI220500","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T12:14:48Z","timestamp":1653480888000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI220500"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,25]]},"ISBN":["9781643682846","9781643682853"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti220500","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,25]]}}}