Predicting Perceived Vocal Roughness Using a Bio-Inspired Computational Model of Auditory Temporal Envelope Processing
Yeonggwang Park, Supraja Anand, Erol J. Ozmeral, Rahul Shrivastav, David A. Eddins
Abstract
Purpose: Vocal roughness is often present in many voice disorders but the assessment of roughness mainly depends on the subjective auditory-perceptual evaluation and lacks acoustic correlates. This study aimed to apply the concept of roughness in general sound quality perception to vocal roughness assessment and to characterize the relationship between vocal roughness and temporal envelop fluctuation measures obtained from an auditory model. Method: Ten /ɑ/ recordings with a wide range of roughness were selected from an existing database. Ten listeners rated the roughness of the recordings in a single-variable matching task. Temporal envelope fluctuations of the recordings were analyzed with an auditory processing model of amplitude modulation that utilizes a modulation filterbank of different modulation frequencies. Pitch strength and the smoothed cepstral peak prominence were also obtained for comparison. Results: Individual simple regression models yielded envelope standard deviation from a modulation filter with a low center frequency (64.3 Hz) as a statistically significant predictor of vocal roughness with a strong coefficient of determination ( r 2 = .80). Pitch strength and CPPS were not significant predictors of roughness. Conclusion: This result supports the possible utility of envelope fluctuation measures from an auditory model as objective correlates of vocal roughness.