{"title":"Speech Technology for Automatic Recognition and Assessment of Dysarthric Speech: An Overview.","authors":"Chitralekha Bhat, Helmer Strik","doi":"10.1044/2024_JSLHR-23-00740","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>In this review article, we present an extensive overview of recent developments in the area of dysarthric speech research. One of the key objectives of speech technology research is to improve the quality of life of its users, as evidenced by the focus of current research trends on creating inclusive conversational interfaces that cater to pathological speech, out of which dysarthric speech is an important example. Applications of speech technology research for dysarthric speech demand a clear understanding of the acoustics of dysarthric speech as well as of speech technologies, including machine learning and deep neural networks for speech processing.</p><p><strong>Method: </strong>We review studies pertaining to speech technology and dysarthric speech. Specifically, we discuss dysarthric speech corpora, acoustic analysis, intelligibility assessment, and automatic speech recognition. We also delve into deep learning approaches for automatic assessment and recognition of dysarthric speech. Ethics committee or institutional review board did not apply to this study.</p><p><strong>Conclusions: </strong>Overcoming the challenge of limited data and exploring new avenues in data collection, artificial intelligence-powered analysis and teletherapy hold immense potential for significant advancements in dysarthria research. To make longer and faster strides, researchers typically rely on existing research and data on a global scale. Therefore, it is imperative to consolidate the existing research and present it in a form that can serve as a basis for future work. In this review article, we have reviewed the contributions of speech technologists to the area of dysarthric speech with a focus on acoustic analysis, speech features, and techniques used. By focusing on the existing research and future directions, researchers can develop more effective tools and interventions to improve communication, quality of life, and overall well-being for people with dysarthria.</p>","PeriodicalId":51254,"journal":{"name":"Journal of Speech Language and Hearing Research","volume":" ","pages":"547-577"},"PeriodicalIF":2.2000,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Speech Language and Hearing Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1044/2024_JSLHR-23-00740","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/15 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: In this review article, we present an extensive overview of recent developments in the area of dysarthric speech research. One of the key objectives of speech technology research is to improve the quality of life of its users, as evidenced by the focus of current research trends on creating inclusive conversational interfaces that cater to pathological speech, out of which dysarthric speech is an important example. Applications of speech technology research for dysarthric speech demand a clear understanding of the acoustics of dysarthric speech as well as of speech technologies, including machine learning and deep neural networks for speech processing.
Method: We review studies pertaining to speech technology and dysarthric speech. Specifically, we discuss dysarthric speech corpora, acoustic analysis, intelligibility assessment, and automatic speech recognition. We also delve into deep learning approaches for automatic assessment and recognition of dysarthric speech. Ethics committee or institutional review board did not apply to this study.
Conclusions: Overcoming the challenge of limited data and exploring new avenues in data collection, artificial intelligence-powered analysis and teletherapy hold immense potential for significant advancements in dysarthria research. To make longer and faster strides, researchers typically rely on existing research and data on a global scale. Therefore, it is imperative to consolidate the existing research and present it in a form that can serve as a basis for future work. In this review article, we have reviewed the contributions of speech technologists to the area of dysarthric speech with a focus on acoustic analysis, speech features, and techniques used. By focusing on the existing research and future directions, researchers can develop more effective tools and interventions to improve communication, quality of life, and overall well-being for people with dysarthria.
期刊介绍:
Mission: JSLHR publishes peer-reviewed research and other scholarly articles on the normal and disordered processes in speech, language, hearing, and related areas such as cognition, oral-motor function, and swallowing. The journal is an international outlet for both basic research on communication processes and clinical research pertaining to screening, diagnosis, and management of communication disorders as well as the etiologies and characteristics of these disorders. JSLHR seeks to advance evidence-based practice by disseminating the results of new studies as well as providing a forum for critical reviews and meta-analyses of previously published work.
Scope: The broad field of communication sciences and disorders, including speech production and perception; anatomy and physiology of speech and voice; genetics, biomechanics, and other basic sciences pertaining to human communication; mastication and swallowing; speech disorders; voice disorders; development of speech, language, or hearing in children; normal language processes; language disorders; disorders of hearing and balance; psychoacoustics; and anatomy and physiology of hearing.