EURASIP Journal on Applied Signal Processing
Volume 2006 (2006), Article ID 34970, 17 pages
doi:10.1155/ASP/2006/34970
Blind Separation of Acoustic Signals Combining SIMO-Model-Based Independent Component Analysis and Binary Masking
1Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma 630-0192, Japan
2Kobe Steel, Ltd., Kobe 651-2271, Japan
Received 1 January 2006; Revised 22 June 2006; Accepted 22 June 2006
Copyright © 2006 Yoshimitsu Mori et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.