Blind speech extraction combining generalized MMSE STSA estimator and ICA-based noise and speech probability density function estimations

Authors:
Hiroshi Saruwatari;Ryoi Okamoto;Yu Takahashi;Kiyohiro Shikano
Affiliations:
Nara Institute of Science and Technology, Ikoma, Nara, Japan;Nara Institute of Science and Technology, Ikoma, Nara, Japan;Nara Institute of Science and Technology, Ikoma, Nara, Japan;Nara Institute of Science and Technology, Ikoma, Nara, Japan
Venue:
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
Year:
2010

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Abstract

In this paper, we propose a new blind speech extraction method combining ICA-based dynamic noise estimation and a generalized minimum meansquare-error short-time spectral amplitude estimator of the target speech. To deal with various types of speech signals with di??erent probability density functions (p.d.f.), we also introduce a spectral-subtraction-based speech p.d.f. estimation and provide a theoretical justification of the proposed approach. We conduct an experiment in an actual railway-station environment, and show the improved noise reduction of the proposed method by objective and subjective evaluations.