A Study of Peak Finding Algorithms for the Autocorrelation Function of Speech Signal

Abstract

In this paper, the peak finding algorithms corresponding to the Autocorrelation Function (ACF), which are widely exploited for detecting the pitch of voiced signal, are proposed.According to various researchers, it is well known fact that the estimation of fundamental frequency (F0) in speech signal is not only very important task but quite difficult mission. The proposed algorithms, presented in this paper, are implemented by using many characteristics -such as monotonic increasing function -of ACF function. Thus, the proposed algorithms may be able to estimate both reliable and correct the fundamental frequency as long as the autocorrelation function of speech signal is accurate. Since the proposed algorithms may reduce the computational complexity it can be applied to the real-time processing.

A Study on the Clarity and Cognition of Songs by Soprano Singers - Focused on the Relationship with the Formant Frequencies

“…(2) Where and represent sample mean and sample variance, respectively [13] [14]. The normalization of the signal by equation 3 is relatively high in reliability of the results of the analysis because it preserves the characteristics of the signal well compared to the normalization of the signal by the maximum value of the signal analyzed.…”