Multistage SIMO-Model-Based Blind Source Separation Combining Frequency-Domain ICA and Time-Domain ICA

Satoshi UKAI  Tomoya TAKATANI  Hiroshi SARUWATARI  Kiyohiro SHIKANO  Ryo MUKAI  Hiroshi SAWADA  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E88-A   No.3   pp.642-650
Publication Date: 2005/03/01
Online ISSN: 
DOI: 10.1093/ietfec/e88-a.3.642
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Adaptive Signal Processing and Its Applications)
blind source separation,  microphone array,  independent component analysis,  SIMO model,  

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In this paper, single-input multiple-output (SIMO)-model-based blind source separation (BSS) is addressed, where unknown mixed source signals are detected at microphones, and can be separated, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. This technique is highly applicable to high-fidelity signal processing such as binaural signal processing. First, we provide an experimental comparison between two kinds of SIMO-model-based BSS methods, namely, conventional frequency-domain ICA with projection-back processing (FDICA-PB), and SIMO-ICA which was recently proposed by the authors. Secondly, we propose a new combination technique of the FDICA-PB and SIMO-ICA, which can achieve a higher separation performance than the two methods. The experimental results reveal that the accuracy of the separated SIMO signals in the simple SIMO-ICA is inferior to that of the signals obtained by FDICA-PB under low-quality initial value conditions, but the proposed combination technique can outperform both simple FDICA-PB and SIMO-ICA.