A pitch detection method based on continuous wavelet transform for harmonic signal

Abstract

In order to track a rapid transient of pitch, a required frame length of some conventional pitch detection methods is too long. Although there are wavelet based pitch detection methods which require only a few periods of pitch for a frame, they are not robust enough against noise. This paper proposes a new pitch detection method which can work properly under noisy environments even if a frame duration is short. The proposed method consists of a power level detector, a signal analyzer, an autocorrelator, a voiced-unvoiced detector and a lag time interpolator. The signal analyzer is based on the continuous wavelet transform using a harmonic analyzing wavelet. Usage of the harmonic analyzing wavelet gives us more information about a pitch in a scalogram. Simulations of pitch detection for a harmonic chirp signal and speech signals are performed. Performances are compared with two conventional pitch detection methods, cepstrum and modified correlation methods. As a result, a performance of a pitch detection by the proposed method under a noisy environment is better than that of the other two conventional methods. In particular, the largest improvement of performance is obtained for male voices.