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Quantifying Speech Rhythm Abnormalities in the Dysarthrias

Laurence White
Sven L. Mattys
University of Bristol, Bristol, United Kingdom

Kaitlin Lansford
Arizona State University

Andrew J. Lotto
University of Arizona, Tucson

Stephanie M. Spitzer
Arizona State University

John N. Caviness
Mayo Clinic Arizona, Scottsdale

Contact author: Julie M. Liss, Department of Speech and Hearing Science, Arizona State University, Box 870102, Tempe, AZ 85287-0102. E-mail: julie.liss{at}asu.edu.

Purpose: In this study, the authors examined whether rhythm metrics capable of distinguishing languages with high and low temporal stress contrast also can distinguish among control and dysarthric speakers of American English with perceptually distinct rhythm patterns.

Methods: Acoustic measures of vocalic and consonantal segment durations were obtained for speech samples from 55 speakers across 5 groups (hypokinetic, hyperkinetic, flaccid-spastic, ataxic dysarthrias, and controls). Segment durations were used to calculate standard and new rhythm metrics. Discriminant function analyses (DFAs) were used to determine which sets of predictor variables (rhythm metrics) best discriminated between groups (control vs. dysarthrias; and among the 4 dysarthrias). A cross-validation method was used to test the robustness of each original DFA.

Results: The majority of classification functions were more than 80% successful in classifying speakers into their appropriate group. New metrics that combined successive vocalic and consonantal segments emerged as important predictor variables. DFAs pitting each dysarthria group against the combined others resulted in unique constellations of predictor variables that yielded high levels of classification accuracy.

Conclusions: This study confirms the ability of rhythm metrics to distinguish control speech from dysarthrias and to discriminate dysarthria subtypes. Rhythm metrics show promise for use as a rational and objective clinical tool.

KEY WORDS: dysarthria, speech rhythm, rhythm metrics

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