Communication improves when human or computer listeners adapt to dysarthria

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter reviews methods that improve the ability of human and machine listeners to understand dysarthric speech. Traditionally, a speaker-oriented approach has been the dominant technique to improve the intelligibility of dysarthric speech. Recent work demonstrates the potential of listeners’ role in enhancing intelligibility. For human listeners, a training method called familiarization is evidenced to be effective, especially when the training is structured in a way to maximize perceptual learning. For machine listeners, the accuracy in understanding dysarthric speech can be improved by adaptive machine learning methods, with an initial model that already incorporates information about speakers’ characteristic speech patterns. Future direction to optimize the training results for human and machine listeners is discussed.
Original languageEnglish (US)
Title of host publicationAcoustic Analysis of Pathologies
Subtitle of host publicationFrom Infancy to Young Adulthood
EditorsAmy Neustein, Hemant A. Patil
PublisherDe Gruyter
Pages181-198
Number of pages18
ISBN (Electronic)9781501513169
ISBN (Print)9781501519628
DOIs
StatePublished - Aug 10 2020

Publication series

NameSpeech Technology and Text Mining in Medicine and Health Care
Volume7

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