Sixth International Conference on Spoken Language Processing
(ICSLP 2000)

Beijing, China
October 16-20, 2000

Speaker Feature Extraction from Pitch Information Based on Spectral Subtraction for Speaker Identification

Yoshiroh Itoh, Jun Toyama, Masaru Shimbo

Graduate School of Engineering, Hokkaido University, Japan

Robust speaker feature extraction under noise conditions is an important issue for application of a speaker recognition system. It is well known that LPC cepstrum, which expresses the spectral envelope, is e ective for speaker recognition. This implies that the spectral rough structure is e ective for speaker recognition. However, LPC cepstrum is a noise-sensitive feature. On the other hand, spectral subtraction is an effective speech enhancement method under stationary noise conditions. In this study, we developed a new method for feature extraction based on spectral subtraction and noise robust spectral rough structures, and we evaluated the e ectiveness of the feature extraction method in speaker identification experiments.

Full Paper

Bibliographic reference.  Itoh, Yoshiroh / Toyama, Jun / Shimbo, Masaru (2000): "Speaker feature extraction from pitch information based on spectral subtraction for speaker identification", In ICSLP-2000, vol.2, 310-313.