Acoustic Correlates of Vocal Quality We have investigated the relationship between various voice qualities and several acoustic measures made from the vowel /i/ phonated by subjects with normal voices and patients with vocal disorders. Among the patients (pathological voices), five qualities were investigated: overall severity, hoarseness, breathiness, roughness, and vocal fry. Six acoustic measures were ... Research Article
Research Article  |   June 01, 1990
Acoustic Correlates of Vocal Quality
 
Author Affiliations & Notes
  • L. Eskenazi
    Department of Electrical Engineering, University of Florida
  • D. G. Childers
    Thomson CSF, Malakoff, France
  • D. M. Hicks
    Communicative Disorders, The Cleveland Clinical Foundation
  • Requests for reprints should be sent to D. G. Childers, University of Florida, Mind-Machine Interaction Research Center, Department of Electrical Engineering, Gainesville, FL 32611.
Article Information
Research Articles
Research Article   |   June 01, 1990
Acoustic Correlates of Vocal Quality
Journal of Speech, Language, and Hearing Research, June 1990, Vol. 33, 298-306. doi:10.1044/jshr.3302.298
History: Received December 13, 1988 , Accepted December 11, 1989
 
Journal of Speech, Language, and Hearing Research, June 1990, Vol. 33, 298-306. doi:10.1044/jshr.3302.298
History: Received December 13, 1988; Accepted December 11, 1989

We have investigated the relationship between various voice qualities and several acoustic measures made from the vowel /i/ phonated by subjects with normal voices and patients with vocal disorders. Among the patients (pathological voices), five qualities were investigated: overall severity, hoarseness, breathiness, roughness, and vocal fry. Six acoustic measures were examined. With one exception, all measures were extracted from the residue signal obtained by inverse filtering the speech signal using the linear predictive coding (LPC) technique. A formal listening test was implemented to rate each pathological voice for each vocal quality. A formal listening test also rated overall excellence of the normal voices. A scale of 1–7 was used. Multiple linear regression analysis between the results of the listening test and the various acoustic measures was used with the prediction sums of squares (PRESS) as the selection criteria. Useful prediction equations of order two or less were obtained relating certain acoustic measures and the ratings of pathological voices for each of the five qualities. The two most useful parameters for predicting vocal quality were the Pitch Amplitude (PA) and the Harmonics-to-Noise Ratio (HNR). No acoustic measure could rank the normal voices.

ACKNOWLEDGMENTS
This research was primarily supported by NIH grants NIDCD RO1 DC00577 and NINCDS RO1 NS17078 with additional support from the University of Florida Center of Excellence Program in Information Transfer and Processing, and the Mind-Machine Interaction Research Center.
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