[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.9708/jksci.2016.21.12.131

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

So, Shin-Ae (Dept. Korean Language and Literature, Soongsil University)
Lee, Kang-Hee (Dept. of Digital Media, Soongsil University)
You, Kwang-Bock (School of Electronic Engineering, Soongsil University)
Lim, Ha-Young (School of Electronic Engineering, Soongsil University)
Park, Ji Su (School of Electronic Engineering, Soongsil University)

Publication Information

Journal of the Korea Society of Computer and Information / v.21, no.12, 2016 , pp. 131-137 More about this Journal

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. The speech data, is composed of Korean emotion expressed words, is used for evaluation of their performance. The pitches are measured to compare the performance of proposed algorithms.

Keywords

peak finding algorithms; autocorrelation function; fundamental frequency (F0); monotonic increasing function; speech signal;

Citations & Related Records

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