White, Laurence

Disturbances in speech rhythm are common in dysarthria, and deficit patterns vary among dysarthria subtypes. Attempts to quantify differences in disordered rhythm patterns have met with limited success. Here, we attempt to differentiate various forms of dysarthria using metrics designed to quantify linguistic rhythm on a stress-timed versus syllable-timed continuum. Speakers with hypokinetic, ataxic, hyperkinetic, or mixed flaccid-spastic dysarthria read sentences. Rhythm metrics were calculated for these utterances based on vocalic and consonantal interval durations. Differences among groups were discovered for %V (percentage of utterance duration comprised of vocalic intervals), VarcoV (rate-normalized standard deviation of vocalic interval durations), and nPVI-V (normalized pairwise variability index for vocalic intervals). Differences were independent of variable speaking rates among groups. All dysarthric groups produced rhythm patterns less stress-timed than the control American English speakers, with lower VarcoV and nPVI-V and higher %V. Those with flaccid-spastic dysarthria secondary to amyotrophic lateral sclerosis exhibited a syllable-timed pattern more extreme than even control Spanish speakers, indicating minimal differentiation of stressed and unstressed syllables. These results show that the various types of rhythmic disturbance accompanying dysarthria can be effectively described and distinguished within a stress-/syllable-timed continuum and relative to healthy speech.

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.