Improved pitch detection algorithm for noisy speech

Abstract

We propose a new, robust pitch detection algorithm for speech degraded by additive noise. Our algorithm exploits the high correlation between adjacent pitch periods that does not exist for the segment as a whole and performs well in the vicinity of voiced/unvoiced regions where the local SNR is low. The algorithm works as follows. We first determine an estimate of the pitch period near the short time peak energy where the local SNR is highest. We then adaptively estimate the local pitch period from the peak towards the transition region by using pitch synchronous cross-correlation with an updated waveform. The performance of this new algorithm is compared to the SIFT and CEPSTRUM algorithms.