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

So, Shin-ae (소신애); Kanghee Lee (이강희); Kwang-Bock You (유광복); 임하영; 박지수

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

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2016, 21(12), pp.131-137
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science

So, Shin-ae ¹, Kanghee Lee ¹, Kwang-Bock You ¹, 임하영 ¹, 박지수 ¹

¹숭실대학교

Accredited

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

Citation status

* References for papers published after 2023 are currently being built.

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This paper was written with support from the National Research Foundation of Korea.

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Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65