Estimation of speaker individual spectral envelope for pitch tracking improvement

Pitch estimation has been of great interest for several decades due to many important audio applications, such as music transcription, source separation, and speech coding. There are several approaches in the literature for estimating pitch, many of which make use of short-time spectrum analysis. A recently proposed algorithm, namely the PEFAC algorithm, performs pre-enhancement of speech components in the short time spectrum to yield a robust pitch estimation. This pre-enhancement procedure is based on a function that outlines the spectral envelope of human speech in the universal sense. In this paper, we propose to overcome some limitations of the PEFAC algorithm by employing an alternative enhancement procedure, which uses an estimation of the individual spectral envelope instead of using a universal function. This approach allows better correspondence to the specific speaker's spectral features. Experimental results show that the proposed algorithm outperforms the original PEFAC algorithm, especially in hard conditions such as low SNR and transient noise.