Pitch Detection Method for Noisy Speech Signals Based on Wavelet Transform and Autocorrelation Function

Abstract

Most of the current pitch detection algorithms can not work well under the high noise environment. For this reason, a pitch detection algorithm for noisy speech signals based on wavelet transform and autocorrelation function is proposed. First, the noisy speech signals are decomposed by three-layer wavelet transform in order to get rid of the high frequency noise and obtain the approximate signals which can better describe the periodicity of speech signal. Then, the autocorrelation functions (ACF) of the approximate signals are calculated. Next, the initial pitches are determined according to the peaks of the autocorrelation function. Finally, median filtering is adopted to improve the smoothness of pitch detection. Experiments show that, the proposed algorithm can improve the accuracy of pitch detection in both clean and noisy environments in comparison the ACF approach.