A multi-pitch tracking algorithm for noisy speech

We present a robust algorithm for multi-pitch tracking of noisy speech. Our approach integrates an improved channel and peak selection method, a new integration method for extracting periodicity information across different frequency channels, and a hidden Markov model (HMM) for forming continuous pitch tracks, and as a result, our algorithm can reliably track single and double pitch tracks in a noisy environment. The proposed algorithm is evaluated on a database of speech utterances mixed with various interferences and the results show that our algorithm outperforms existing algorithms significantly.