How Do Voice Perceptual Changes Predict Acoustic Parameters in Persian Voice Patients?

Introduction. Perceptual and acoustic analyses are essential tools that help voice therapists comprehensively assess voice quality. While perceptual evaluations are subjective and are influenced by external and culturally driven factors, acoustic analysis is an objective and reliable means of evaluating voice. The goals of this study were (1) to determine which acoustic parameters were predicted by perceptual voice quality and (2) to assess the effect of a short period of training on the reliability of perceptual voice analyses for Persian speakers. Method. This was a cross-sectional study. Subjects were 20 patients with various voice disorders. Voice samples were obtained during text reading and /a/ prolongation. Fifteen expert voice clinicians completed perceptual evaluations on voice samples using the Grade, Roughness, Breathiness, Asthenia, and Strain scale. We repeated this process after a short period of perceptual voice evaluation training. Acoustic analysis was completed using the Pawl program. We used the intraclass correlation coefficient (ICC) for reliability measurement of the perceptual evaluation results and ordinal regression procedures to analyze all data. Significance level was set at P < 0.05. Results. Both intrarater and interrater reliability increased after training, for all five parameters. The ICC for grade increased to 0.95 after training. Grade and roughness significantly predicted fundamental frequency (F0) (P= 0.021 and P = 0.030, respectively) and harmonic-to-noise ratio (HNR) (P = 0.019 and P = 0.016, respectively). Breathiness significantly predicted shimmer (P= 0.013). Conclusion. Training had a positive effect and increased the reliability of perceptual voice evaluation. For Persian listeners. changes in F0, increases in HNR, and shimmer were perceptually associated with poor voice quality.