Evaluation of pitch estimation algorithms on separated speech

To post-process outputs of speech separation systems with harmonic enhancement, it is normally required to estimate the fundamental frequency. This paper evaluates the performance of a few representative robust pitch estimation algorithms on speech reconstructed from two-speaker mixture signals. The separation outputs obtained by two state-of-the-art single-channel separation algorithms are used for the evaluation. A recently proposed sparsity-based pitch estimation method is applied to the separated speech and a new pitch tracking algorithm is proposed. Experimental results show that on the separated speech the proposed method consistently surpasses the others with significantly low gross error rate, which is similar to the gross error rates of the other methods on clean speech.