Speech Technology for Automatic Recognition and Assessment of Dysarthric Speech: An Overview

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. 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. 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.