Parametric Quantitative Acoustic Analysis of Conversation Produced by Speakers With Dysarthria and Healthy Speakers
Joseph R. Duffy Mayo Clinic, Rochester, MN Contact author: Kristin Rosen, 1500 Highland Avenue, Waisman Center, University of Wisconsin, Madison, WI 53705. Email: rosen{at}waisman.wisc.edu PURPOSE: This study's main purpose was to (a) identify acoustic signatures of hypokinetic dysarthria (HKD) that are robust to phonetic variation in conversational speech and (b) determine specific characteristics of the variability associated with HKD. METHOD: Twenty healthy control (HC) participants and 20 participants with HKD associated with idiopathic Parkinson's disease (PD) repeated 3 isolated sentences (controlled phonetic content) and 2 min of conversational speech (phonetic content treated as a random variable). A MATLAB-based program automatically calculated measures of contrastivity: speechpause ratio, intensity variation, median and maximum formant slope, formant range, change in the upper and lower spectral envelope, and range of the spectral envelope. t tests were used to identify which measures were sensitive to HKD and which measures differed by task. Discriminant analysis was used to identify the combination of measures that best predicted HKD, and this analysis was then used as a general measure of contrastivity (Contrastivity Index). Differential effects of HKD on maximum and typical contrastivity levels were tested with interaction of maximum, minimum, and median observations of individual speakers and with pairwise comparisons of skewness and kurtosis of the contrastivity index distributions. RESULTS: Group differences were detected with pairwise comparisons with t tests in 8 of the 9 measures. Percentage pause time and spectral range were identified as the most specific (95%) and accurate (95%) differentiators of HKD and HC conversational speech. Sentence repetition elicited significantly higher levels of contrastivity than conversational speech in both HC and HKD speakers. Maximum and minimum contrastivities were significantly lower in HKD speech, but there was no evidence that HKD affects maximum contrastivity levels more than median contrastivity levels. The HKD speakers' contrastivity distributions were significantly more skewed to lower levels of production. CONCLUSION: HKD can be consistently distinguished from HC speech in both sentence repetition and conversational speech on the basis of intensity variation and spectral range. Although speakers with HKD were effectively able to produce higher contrastivity levels in sentence repetition tasks, they habitually performed closer to the lower end of their production ranges. KEY WORDS: acoustic, dysarthria, conversation, stability, distributional analysis, Parkinson's disease CiteULike Connotea Del.icio.us Digg Facebook Reddit Technorati Twitter What's this?.
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Erscheinungsjahr: |
2006 |
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Erschienen: |
2006 |
Enthalten in: |
Zur Gesamtaufnahme - volume:49 |
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Enthalten in: |
Journal of speech, language, and hearing research - 49(2006), 2, Seite 395-411 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Rosen, Kristin M [VerfasserIn] |
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Volltext |
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doi: |
10.1044/1092-4388(2006/031) |
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PPN (Katalog-ID): |
OLC1984067001 |
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520 | |a Joseph R. Duffy Mayo Clinic, Rochester, MN Contact author: Kristin Rosen, 1500 Highland Avenue, Waisman Center, University of Wisconsin, Madison, WI 53705. Email: rosen{at}waisman.wisc.edu PURPOSE: This study's main purpose was to (a) identify acoustic signatures of hypokinetic dysarthria (HKD) that are robust to phonetic variation in conversational speech and (b) determine specific characteristics of the variability associated with HKD. METHOD: Twenty healthy control (HC) participants and 20 participants with HKD associated with idiopathic Parkinson's disease (PD) repeated 3 isolated sentences (controlled phonetic content) and 2 min of conversational speech (phonetic content treated as a random variable). A MATLAB-based program automatically calculated measures of contrastivity: speechpause ratio, intensity variation, median and maximum formant slope, formant range, change in the upper and lower spectral envelope, and range of the spectral envelope. t tests were used to identify which measures were sensitive to HKD and which measures differed by task. Discriminant analysis was used to identify the combination of measures that best predicted HKD, and this analysis was then used as a general measure of contrastivity (Contrastivity Index). Differential effects of HKD on maximum and typical contrastivity levels were tested with interaction of maximum, minimum, and median observations of individual speakers and with pairwise comparisons of skewness and kurtosis of the contrastivity index distributions. RESULTS: Group differences were detected with pairwise comparisons with t tests in 8 of the 9 measures. Percentage pause time and spectral range were identified as the most specific (95%) and accurate (95%) differentiators of HKD and HC conversational speech. Sentence repetition elicited significantly higher levels of contrastivity than conversational speech in both HC and HKD speakers. Maximum and minimum contrastivities were significantly lower in HKD speech, but there was no evidence that HKD affects maximum contrastivity levels more than median contrastivity levels. The HKD speakers' contrastivity distributions were significantly more skewed to lower levels of production. CONCLUSION: HKD can be consistently distinguished from HC speech in both sentence repetition and conversational speech on the basis of intensity variation and spectral range. Although speakers with HKD were effectively able to produce higher contrastivity levels in sentence repetition tasks, they habitually performed closer to the lower end of their production ranges. KEY WORDS: acoustic, dysarthria, conversation, stability, distributional analysis, Parkinson's disease CiteULike Connotea Del.icio.us Digg Facebook Reddit Technorati Twitter What's this? | ||
540 | |a Nutzungsrecht: © COPYRIGHT 2006 American Speech-Language-Hearing Association | ||
650 | 4 | |a Discriminant Analysis | |
650 | 4 | |a Phonetics | |
650 | 4 | |a Humans | |
650 | 4 | |a Sound Spectrography | |
650 | 4 | |a National Library of Medicine | |
650 | 4 | |a Aged | |
650 | 4 | |a Multivariate Analysis | |
650 | 4 | |a Dysarthria: physiopathology | |
650 | 4 | |a Speech Production Measurement | |
650 | 4 | |a Speech Acoustics | |
650 | 4 | |a Aged, 80 and over | |
650 | 4 | |a Adult | |
650 | 4 | |a Case-Control Studies | |
650 | 4 | |a Middle Aged | |
650 | 4 | |a Parkinson Disease: complications | |
650 | 4 | |a Speech | |
650 | 4 | |a Male | |
650 | 4 | |a Dysarthria: etiology | |
650 | 4 | |a Dysarthria - physiopathology | |
650 | 4 | |a Parkinson Disease - complications | |
650 | 4 | |a Dysarthria - etiology | |
650 | 4 | |a Conversation | |
650 | 4 | |a Causes of | |
650 | 4 | |a Articulation disorders | |
650 | 4 | |a Analysis | |
650 | 4 | |a Parameter estimation | |
650 | 4 | |a Statistical analysis | |
650 | 4 | |a Speech disorders | |
650 | 4 | |a Acoustics | |
650 | 4 | |a Parkinsons disease | |
700 | 1 | |a Kent, Raymond D |4 oth | |
700 | 1 | |a Delaney, Amy L |4 oth | |
700 | 1 | |a Duffy, Joseph R |4 oth | |
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