Pitch tracking based on statistical anticipation
Mingyang Wu, Deliang Wang, Guy J. Brown · 2002
An effective multipitch tracking algorithm for noisy speech is critical for auditory processing. However, the performance of existing algorithms is not satisfactory. We have developed a robust algorithm for multipitch tracking of noisy speech based on statistical anticipation. By combining an improved channel and peak selection method, a new integration method for extracting periodicity information across the different channels, and a hidden Markov model (HMM) for forming continuous pitch tracks, our algorithm can reliably track single and double pitch tracks in a noisy environment.