The Exploration of an Objective Model for Roughness With Several Acoustic Markers

Objective: In voice assessment, the evaluation of voice quality is a major component in which roughness has received wide acceptance as a major subtype of abnormal voice quality. The aim of the present study was to develop a new multivariate acoustic model for the evaluation of roughness. Method: In total, 970 participants with dysphonia and 88 participants with normal voice were included. Concatenated voice samples of continuous speech and sustained vowel [a:] were perceptually judged on roughness severity. Acoustic analyses were conducted on the voiced segments of the continuous speech sample plus sustained vowel as well. A stepwise multiple linear regression analysis was applied to construct an acoustic model of the best acoustic predictors. Concurrent validity, diagnostic accuracy, and cross-validation were verified on the basis of Spearman correlation coefficient (r_s), several estimates of the receiver operating characteristics plus the likelihood ratio, and iterated internal cross-correlations. Results: Six experts were included for perceptual analysis based on acceptable rater reliability. Stepwise multiple regression analysis yielded a 12-variable acoustic model. A marked correlation was identified between the model and the perceptual judgment (r_s = 0.731, P = 0.000). The cross-correlations confirmed a high comparable degree of association. However, the receiver operating characteristics and likelihood ratio results showed the best diagnostic outcome at a threshold of 2.92, with a sensitivity of 51.9% and a specificity of 94.9%. Conclusions: Currently, the newly developed roughness model is not recommended for clinical practice. Further research is needed to detect the acoustic complexity of roughness (eg, multiplophonia, irregularity, chaotic structure, glottal fry, etc).