Predicting Voice Disorder Status From Smoothed Measures of Cepstral Peak Prominence Using Praat and Analysis of Dysphonia in Speech and Voice (ADSV).
OBJECTIVE
The purposes of this study were to (1) determine and compare the diagnostic accuracy of a single acoustic measure, smoothed cepstral peak prominence (CPPS), to predict voice disorder status from connected speech samples using two software systems: Analysis of Dysphonia in Speech and Voice (ADSV) and Praat; and (2) to determine the relationship between measures of CPPS generated from these programs.


METHODS
This is a retrospective cross-sectional study.


METHODS
Measures of CPPS were obtained from connected speech recordings of 100 subjects with voice disorders and 70 nondysphonic subjects without vocal complaints using commercially available ADSV and freely downloadable Praat software programs. Logistic regression and receiver operating characteristic (ROC) analyses were used to evaluate and compare the diagnostic accuracy of CPPS measures. Relationships between CPPS measures from the programs were determined.


RESULTS
Results showed acceptable overall accuracy rates (75% accuracy, ADSV; 82% accuracy, Praat) and area under the ROC curves (area under the curve [AUC] = 0.81, ADSV; AUC = 0.91, Praat) for predicting voice disorder status, with slight differences in sensitivity and specificity. CPPS measures derived from Praat were uniquely predictive of disorder status above and beyond CPPS measures from ADSV (χ2(1) = 40.71, P < 0.001). CPPS measures from both programs were significantly and highly correlated (r = 0.88, P < 0.001).


CONCLUSIONS
A single acoustic measure of CPPS was highly predictive of voice disorder status using either program. Clinicians may consider using CPPS to complement clinical voice evaluation and screening protocols.
Department of Speech and Hearing Sciences, University of Washington, Seattle, Washington. Electronic address: csauder2@uw.edu.
Cara
C
Sauder
Department of Speech and Hearing Sciences, University of Washington, Seattle, Washington.
Michelle
M
Bretl
Department of Speech and Hearing Sciences, University of Washington, Seattle, Washington.
Tanya
T
Eadie
D000162:Acoustics; D000328:Adult; D019540:Area Under Curve; D016009:Chi-Square Distribution; D003430:Cross-Sectional Studies; D055154:Dysphonia / Q000175:diagnosis* / Q000503:physiopathology; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D011237:Predictive Value of Tests; D012372:ROC Curve; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012815:Signal Processing, Computer-Assisted; D012984:Software; D013061:Speech Acoustics; D013068:Speech Production Measurement / Q000379:methods*; D014827:Vocal Cords / Q000503:physiopathology*; D014833:Voice Quality
Acoustic measures; Analysis of Dysphonia in Speech and Voice; Dysphonia; Praat; Smoothed cepstral peak prominence