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.

This study is the third in a series that has explored the source of intelligibility decrement in dysarthria by jointly considering signal characteristics and the cognitive–perceptual processes employed by listeners. A paradigm of lexical boundary error analysis was used to examine this interface by manipulating listener constraints with a brief familiarization procedure. If familiarization allows listeners to extract relevant segmental and suprasegmental information from dysarthric speech, they should obtain higher intelligibility scores than nonfamiliarized listeners, and their lexical boundary error patterns should approximate those obtained in misperceptions of normal speech. Listeners transcribed phrases produced by speakers with either hypokinetic or ataxic dysarthria after being familiarized with other phrases produced by these speakers. Data were compared to those of nonfamiliarized listeners [Liss et al., J. Acoust. Soc. Am. 107, 3415–3424 (2000)]. The familiarized groups obtained higher intelligibility scores than nonfamiliarized groups, and the effects were greater when the dysarthria type of the familiarization procedure matched the dysarthria type of the transcription task. Remarkably, no differences in lexical boundary error patterns were discovered between the familiarized and nonfamiliarized groups. Transcribers of the ataxic speech appeared to have difficulty distinguishing strong and weak syllables in spite of the familiarization. Results suggest that intelligibility decrements arise from the perceptual challenges posed by the degraded segmental and suprasegmental aspects of the signal, but that this type of familiarization process may differentially facilitate mapping segmental information onto existing phonological categories.

Purpose: Previous research demonstrated the ability of temporally based rhythm metrics to distinguish among dysarthrias with different prosodic deficit profiles (J. M. Liss et al., 2009). The authors examined whether comparable results could be obtained by an automated analysis of speech envelope modulation spectra (EMS), which quantifies the rhythmicity of speech within specified frequency bands.Method: EMS was conducted on sentences produced by 43 speakers with 1 of 4 types of dysarthria and healthy controls. The EMS consisted of the spectra of the slow-rate (up to 10 Hz) amplitude modulations of the full signal and 7 octave bands ranging in center frequency from 125 to 8000 Hz. Six variables were calculated for each band relating to peak frequency and amplitude and relative energy above, below, and in the region of 4 Hz. Discriminant function analyses (DFA) determined which sets of predictor variables best discriminated between and among groups.Results: Each of 6 DFAs identified 2–6 of the 48 predictor variables. These variables achieved 84%–100% classification accuracy for group membership.Conclusions: Dysarthrias can be characterized by quantifiable temporal patterns in acoustic output. Because EMS analysis is automated and requires no editing or linguistic assumptions, it shows promise as a clinical and research tool.

Vowel space area (VSA) is an attractive metric for the study of speech production deficits and reductions in intelligibility, in addition to the traditional study of vowel distinctiveness. Traditional VSA estimates are not currently sufficiently sensitive to map to production deficits. The present report describes an automated algorithm using healthy, connected speech rather than single syllables and estimates the entire vowel working space rather than corner vowels. Analyses reveal a strong correlation between the traditional VSA and automated estimates. When the two methods diverge, the automated method seems to provide a more accurate area since it accounts for all vowels.

This investigation is the second in a series to examine a potential source of reduced intelligibility in dysarthric speech, namely the mismatch between listeners’ perceptual strategies and the acoustic information available in the dysarthric speech signal. Lexical boundary error (LBE) analysis was conducted on listener transcripts from phrases produced by speakers with hypokinetic dysarthria, ataxic dysarthria, and normal controls. By design, the hypokinetic and ataxic dysarthric tapes elicited similar intelligibility (words-correct) scores. However, they elicited different numbers and patterns of lexical boundary errors. The nature of the error pattern differences can be traced to the listeners’ use of available syllabic strength information to segment the acoustic stream. Specifically, although both dysarthric speech samples elicited numerous lexical boundary errors, those for the hypokinetic speech generally conformed to predictions offered from studies of degraded normal speech. Those for the ataxic speech did not conform strongly to such predictions. It appears that the prosodic deficits of the ataxic speech (tendency toward syllabic isochrony, excessive loudness variation, and reduced vowel working space consequent to reductions in vowel strength) posed more of a problem for listeners than did the prosodic deficits of the hypokinetic speech (rapid rate, monotony, reduced vowel working space).