Screening of Voice Pathologies: Identifying the Predictive Value of Voice Acoustic Parameters for Common Voice Pathologies

Abstract

Voice acoustic analysis is important for objectively assessing voice production and diagnosing voice disorders. This study aimed to investigate the sensitivity of various voice acoustic parameters in differentiating common voice pathology types. Data from the publicly available Perceptual Voice Qualities Database were analyzed; the database includes recordings of participants with and without voice disorders. A wide range of acoustic parameters was estimated from the recordings, such as alpha ratio, harmonics-to-noise ratio (HNR), cepstral peak prominence smoothed (CPPS), pitch period entropy (PPE), fundamental frequency, jitter, shimmer, and sound pressure levels. The predictive capabilities of the parameters were evaluated using receiver operating characteristic curves. Linear regression analysis determined the associations between parameters and voice disorders. Principal component analysis was conducted to identify important parameters for distinguishing voice disorders. This study has identified significant differences in acoustic parameters between those with and without voice disorders. Notably, the combination of five parameters-namely, PPE, shimmer, jitter, CPPS, and HNR-was identified as a strong predictor in voice disorder screening. These findings contribute substantially to the field of voice disorders, offering valuable insights for screening and diagnosis.