Despite slight differences in sensitivity and specificity, Sauder et.
Upgrade cepstral voices software#
reported an accuracy of 82% for CPPS in predicting the presence of a voice disorder in connected speech samples when applying the software Praat, and a 75% accuracy for the software ADSV. The authors concluded that regardless of the language analysed, CPP values could be transformed between programs with relatively small prediction errors 3. (2017) reported a strong parallel-forms reliability for CPP. For these two software systems, Watts et al. In practice, researchers and clinicians often compute CPP using custom algorithms, as provided in commercial software packages such as ADSV (PENTAX Medical Corporation), or freely available software such as PRAAT 10. In a variety of studies, CPP has been shown to be correlated with dysphonia severity and was described as an index of the harmonicity of an acoustic signal 1- 6. Acoustic signals with a clear harmonic structure show a more prominent cepstral peak, whereas dysphonic, aperiodic, or breathy voice signals have a reduced cepstral peak. In regular or Type 1 voice signals, the first cepstral peak (also first rahmonic) corresponds to the fundamental frequency period 1, 2, 4, 9. The Smoothed Cepstral Peak Prominence (CPPS) is a variant of CPP with an additional processing step of smoothing the individual cepstra in the temporal and spectral domains before calculating the peak prominence 2, 8. CPP indicates the difference (in dB) between the first rahmonic gamnitude and the point of a regression line fitted across the cepstrum that crosses the quefrency of the first rahmonic 2, 4. In a popular diagnostic application of CPP, the computation is derived from the power spectrum of the power spectrum of an acoustic voice signal.
0 kommentar(er)
