Blind separation of acoustic signals combining SIMO-model-based independent component analysis and binary masking

Authors:
Yoshimitsu Mori;Hiroshi Saruwatari;Tomoya Takatani;Satoshi Ukai;Kiyohiro Shikano;Takashi Hiekata;Youhei Ikeda;Hiroshi Hashimoto;Takashi Morita
Affiliations:
Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma, Japan;Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma, Japan;Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma, Japan;Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma, Japan;Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma, Japan;Kobe Steel, Ltd., Kobe, Japan;Kobe Steel, Ltd., Kobe, Japan;Kobe Steel, Ltd., Kobe, Japan;Kobe Steel, Ltd., Kobe, Japan
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2006

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Abstract

A new two-stage blind source separation (BSS) method for convolutive mixtures of speech is proposed, in which a single-input multiple-output (SIMO)-model-based independent component analysis (ICA) and a new SIMO-model-based binary masking are combined. SIMO-model-based ICA enables us to separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources in their original form at the microphones. Thus, the separated signals of SIMO-model-based ICA can maintain the spatial qualities of each sound source. Owing to this attractive property, our novel SIMO-model-based binary masking can be applied to efficiently remove the residual interference components after SIMO-model-based ICA. The experimental results reveal that the separation performance can be considerably improved by the proposed method compared with that achieved by conventional BSS methods. In addition, the real-time implementation of the proposed BSS is illustrated.