###### Abstract  
Cepstral peak prominence-smoothed (CPPs) and long-term average spectrum (LTAS) are robust measures that represent the glottal source and source-filter interactions, respectively. Until now, little has been known about how physiological events impact auditory-perceptual characteristics in the objective measures of CPPs and LTAS (alpha ratio; L1-L0). Thus, this paper aims to analyze the relationship between such acoustic measures and auditory-perceptual analysis and then determine which acoustic measure best represents voice quality. We analyzed 53 voice samples of vocally healthy participants (vocally healthy group-VHG) and 49 voice samples of participants with behavioral dysphonia (dysphonic group-DG). Each voice sample was composed of sustained vowel /a/ and connected speech. CPPs seem to be the best predictor of voice deviation in both studied populations because there was moderate to strong negative correlations with general degree, breathiness, roughness, and strain (auditory-perceptual parameters). Regarding L1-L0, this measure is related to breathiness (moderate negative correlations). Hence, L1-L0 provides information about air leak through closed glottis, assisting the phonatory efficiency analysis. acoustic signal processing; speech signal processing; voice quality; communication; dysphonia; auditory-perceptual analysis +
Footnote †: journal: Medical  
that, in nearly normal voices, has low perturbations of the acoustic signal [4]. The source signal periodicity or aperiodicity can be analyzed by using time-based measures [5; 6], i.e., jitter and shimmer, that measure the cycle-to-cycle boundary deviation of frequency and intensity, respectively [7; 8; 9]. It can also be analyzed by using frequency-based measures, i.e., cepstral peak prominence (CPP) [10; 11]. Since time-based measures require nearly periodic signals (type I) and exact measurement of the fundamental frequency, their reliability is questionable in more than mild disturbed vocal signals (types II and III). However, most vocal disorders have a greater aperiodicity level, making the use of these measures questionable [12; 13]. Among frequency-based measures, according to [PERSON] and [PERSON] [14], CPP is calculated by using an inverse Fast Fourier Transform (FFT) of the log power spectrum of a voice signal. That means it is determined by measuring the amplitude (dB) difference from the most prominent cepstral peak to the regression line drawn direct below this peak. In other words, the cepstrum generated through spectral analysis of a spectrum produces a peak that corresponds to the dominant rahmonic (i.e., anagram for harmonic) associated with the fundamental frequency (F\({}_{0}\)), the first harmonic, of the voice [9]. Thus, voices with nearly periodic signals have a better harmonic definition, which means a higher CPP [9; 11; 15]. Furthermore, since CPP is extracted from frames instead of cycles, it is more reliable for analyzing voices with moderate to intense deviations [10], i.e., type II and III signals. A CPP variation is called cepstral peak prominence-smoothed (CPPs) and has different calculation algorithms, such as smoothing the cepstrum before extracting the peak and using 1024 frames every 2 ms instead of 10 ms, which makes CPPs more robust and with no influence of artifacts [15]. On the other hand, one advantage of CPP and CPPs regarding time-based measures is the possibility of applying them in continuous speech [4; 15; 16; 17]. [PERSON] et al. [4] analyzed CPP and CPPs differences between vocally healthy and dysphonic women. They found that dysphonic women had lower CPP and CPPs values. As a complementary analysis, they discovered that the acoustic analysis had a moderate negative correlation with general degree and breathiness parameters of vocal quality. At last, they suggest including men in these analyses to better understand these measures. [PERSON], [PERSON], and [PERSON] [17] analyzed the correlations between CPPs and auditory-perceptual parameters in participants with vocal fold unilateral paralysis.