title: The relationship between perceptual disturbances in dysarthric speech and automatic speech recognition performance.
abstract: State-of-the-art automatic speech recognition (ASR) engines perform well on healthy speech; however recent studies show that their performance on dysarthric speech is highly variable. This is because of the acoustic variability associated with the different dysarthria subtypes. This paper aims to develop a better understanding of how perceptual disturbances in dysarthric speech relate to ASR performance. Accurate ratings of a representative set of 32 dysarthric speakers along different perceptual dimensions are obtained and the performance of a representative ASR algorithm on the same set of speakers is analyzed. This work explores the relationship between these ratings and ASR performance and reveals that ASR performance can be predicted from perceptual disturbances in dysarthric speech with articulatory precision contributing the most to the prediction followed by prosody.
authors.affiliation: Department of Speech and Hearing Science, Arizona State University, Tempe, Arizona 85287, USA.
authors.forename: Ming
authors.initials: M
authors.lastname: Tu
authors.affiliation: School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, USAmingtu@asu.edu, awisler@asu.edu, visar@asu.edu, jmliss@asu.edu.
authors.forename: Alan
authors.initials: A
authors.lastname: Wisler
authors.affiliation: Department of Speech and Hearing Science, Arizona State University, Tempe, Arizona 85287, USA.
authors.forename: Visar
authors.initials: V
authors.lastname: Berisha
authors.affiliation: Department of Speech and Hearing Science, Arizona State University, Tempe, Arizona 85287, USA.
authors.forename: Julie M
authors.initials: JM
authors.lastname: Liss
mesh_terms: D000465:Algorithms; D004401:Dysarthria; D006801:Humans; D013060:Speech; D013065:Speech Intelligibility; D013068:Speech Production Measurement; D049250:Speech Recognition Software