Pitch detection of speech signals in noisy environment by wavelet

The pitch of voiced speech sounds provides very important information in speech analysis. Pitch estimation is a difficult task when unprevented noise exists. However experimental results have shown that even robust pitch detection techniques fail in noisy environment with periodic patterns such as noise generated by machines. Wavelet transform, with its special properties in time frequency relation, can be used to detect pitch with remarkable advantage in noise resistance. In wavelet signal analysis, the modulus of the transform have been used extensively, however, we found that the phase information is equally important especially for pitch detection. Since the phase spectrum is always intensive to noise, a more promising pitch period can be obtained from the phase diagram. Properties of the phase pattern in wavelet transform are investigated and the result is applied to construct a robust pitch detector. In our first test, the detector is employed to detect the pitches of a set of speech signals with white noise. We found that our approach clearly outperforms other non-wavelet methods with low signal-to-noise ratio. Sinusoidal noise with different frequency levels is used in the second test. Simulation results have shown that our system works quite stable in such an environment.