Acoustic and Psychoacoustic Correlates of Perceived Vocal Strain
Channel: Supraja Anand
Date: 2020-05-16

David A. Eddins, Ph.D., CCC-A
Supraja Anand, Ph.D.
Madison Dyjak, B.A.
Rahul Shrivastav, Ph.D., CCC-SLP

Abstract
Objective: Few systematic studies have investigated the relationship between acoustic and perceptual correlates of vocal strain and possible acoustic and perceptual correlates. Such correlates may be limited by the co-occurrence of multiple voice qualities. The goal of this study is to determine the potential influence of co-occurring breathiness on strain perception.  

Methods: A large set of dysphonic voices were categorized by experts into voices perceived to be primarily strained and voices perceived to have strain along with breathiness. A subset of 18 voices per category were chosen to represent a wide continuum of strain severity based on a visual sort ranking (VSR) procedure. Ten listeners rated 540 /a/ vowels (18 voices x 10 repetitions x 3 trials) per category on a magnitude estimation (ME) task. Predictors of vocal strain included six spectral moment measures computed on a linear scale or from the output of an auditory processing front-end (Bark, excitation, and specific loudness). Sharpness was computed as the first moment of the specific loudness function expressed as a function of critical-band rate. Cepstral peak prominence, pitch height, and pitch strength also served as predictors. 

Results: There was a high correlation between the VSR rankings of two experts for both categories of strain voices. Data also indicated high intra- and inter-listener reliability on perceived strain magnitudes. Significant differences were observed in sharpness, some of the transformed spectral energy metrics, CPP, and pitch strength between the two categories of strain. Additional regression analyses will be completed to evaluate the relationship between acoustic predictors and the perceived strain magnitudes from the ME tasks. 

Conclusions: Results of this study will aid in the development of computational models that account for covariance in voice qualities and will help to identify a suitable comparison stimulus for matching tasks to evaluate perception of strain.