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Objective Indices of Perceived Vocal Strain
Supraja Anand1, Lisa M Kopf2, Rahul Shrivastav3
1Department of Communication Sciences and Disorders, University of South Florida, Tampa, Florida.
Journal of Voice : Official Journal of the Voice Foundation
|August 2, 2018
Summary
Strain perception in voice disorders is better understood by analyzing acoustic and psychoacoustic measures. Modeling with an auditory processing front-end accurately characterizes perceived strain, improving diagnosis for conditions like vocal fold paralysis.
Area of Science:
- Voice Science
- Acoustic Phonetics
- Psychoacoustics
Background:
- Strain is a common voice quality in various disorders, yet understudied compared to breathiness and roughness.
- Hyperfunctional voice disorders, spasmodic dysphonia, and vocal fold paralysis often present with vocal strain.
Purpose of the Study:
- To identify and explore acoustic and psychoacoustic measures underlying the perception of vocal strain.
- To establish a perceptual basis for understanding and quantifying vocal strain.
Main Methods:
- Listeners rated the degree of strain in 28 dysphonic voice samples on a five-point scale.
- Computational acoustic measures, including cepstrum and spectral moments, were correlated with perceptual ratings.
- Auditory processing front-end transformations were applied to acoustic signals before analysis.
Main Results:
- Perceived strain strongly correlated with cepstral peak prominence, sharpness, and specific spectral metrics.
- Auditory processing front-end measures (excitation pattern, specific loudness) combined with cepstral measures explained 77-79% of the variance in perceived strain.
- The sharpness model by Fastl and Zwicker (2007) emerged as a significant predictor of strain perception.
Conclusions:
- Modeling vocal strain perception with an auditory front-end enhances characterization of perceptual ratings.
- This approach aligns with previous findings for breathiness and roughness, offering a unified analysis framework.
- Results validate the sharpness model's utility in predicting perceived vocal strain.
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