Monaural Speech Segregation Based on Improved Pitch Tracking Method

By means of the feature that humans can distinguish and track speech signal of interest under various noisy environments, the speech segregation system based on computational auditory scene analysis (CASA) has obtained considerable development in recent years. How to correctly pitch detection in noisy environment has been a challenge in CASA system. Hence, in this paper, an improved pitch tracking algorithm based on target source is proposed. By estimating the target units and detecting the pitch periods iteratively, the proposed algorithm obtains pitch tracks. By comparing with conventional pitch tracking method under various interferences, it is shown that the proposed algorithm can effectively suppress the interferences and improve the average output SNR and the quality of segregated speech.