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Research Article|Articles in Press

Investigation of the Cepstral Spectral Acoustic Analysis for Classifying the Severity of Dysphonia

Published:January 30, 2023DOI:https://doi.org/10.1016/j.jvoice.2022.12.012

      Summary

      Objectives

      The advantages of cepstral measurements in the evaluation of dysphonia have been noted in previous studies. However, there is an unclarity regarding the results of cepstral analyzes effect in determining the severity of dysphonia. The aims of this study were to determine the cut-off values of cepstral peak prominence, cepstral peak prominence standard deviation, low frequency/ high frequency ratio, low frequency/high frequency ratio standard deviation, and cepstral spectral index of dysphonia for predicting the voice severity within a Turkish speaking population, as well as to confirm the discriminative power of these cut-off values.

      Materials Methods

      One hundred ninety-five individuals with voice disorders and an equal number of age and gender-matched individuals without voice disorders were included. Included subjects had visited the Hacettepe University Hospitals Speech and Language Therapy Department for voice evaluation between January 2017 and September 2021. The voice recordings from all participants included the six CAPE-V/Turkish sentences and sustained vowel /a/. Three raters provided auditory perceptual ratings of the voice samples using the GRBAS scale (grade) and overall severity for the CAPE-V/Turkish. Participants were categorized into normal and mild, moderate, and severely dysphonic groups based on the auditory perceptual evaluation. Analysis of Dysphonia in Speech and Voice (ADSV) software was used for cepstral spectral acoustic analysis.

      Results

      In the sustained vowel context, the area under the curve (ROC) for the CSID value was >0.8, except for mild vs. moderate dysphonia groups. In connected speech contexts, the ROC of the CPP value was also >0.8, except for normal vs. mild dysphonia groups. The cut-off values of CPP and CSID demonstrated high sensitivity and specificity for predicting voice severities.

      Conclusion

      The cut-off values for the parameters that predicted voice severities showed a significant degree of discriminative power for categorizing voice severities among Turkish-speaking people.

      Key Words

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