Extraction of pitch information in noisy speech using wavelet transform with aliasing compensation

Although many wavelet-based pitch detection methods have been proposed in the literature, there still remains a need to investigate new wavelet-based methods for more accurate and more robust pitch determination. In this paper, an improved wavelet-based method is developed for extraction of pitch information in noisy speech. At each decomposition in the wavelet transform, an aliasing compensation algorithm is applied to approximate and detail signals, in which the distortion of aliasing due to downsampling and upsampling operations of the wavelet transform is eliminated. In addition, this paper utilizes the concept of spatial correlation function used in signal denoising to improve the performance of pitch detection in a noisy environment. It is shown in various experimental results that this new type of method has a considerable performance improvement compared with other conventional methods and wavelet-based methods