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EURASIP Journal on Applied Signal Processing 2003:11, 1091–1109 c 2003 Hindawi Publishing

EURASIP Journal on Applied Signal Processing 2003:11, 1091–1109 c 2003 Hindawi Publishing Corporation Exploiting Acoustic Similarity of Propagating Paths for Audio Signal Separation Bin Yin Faculty of Electrical Engineering, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands Storage Signal Processing Group, Philips Research Laboratories, P.O. Box WY-31, 5656 AA Eindhoven, The Netherlands Email: bin.yin@philips.com Piet C. W. Sommen Faculty of Electrical Engineering, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands Email: p.c.w.sommen@tue.nl Peiyu He Faculty of Electrical Engineering, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands University of Sichuan, Chengdu 610064, China Email: hepeiyu@hotmail.com Received. | EURASIP Journal on Applied Signal Processing 2003 11 1091-1109 2003 Hindawi Publishing Corporation Exploiting Acoustic Similarity of Propagating Paths for Audio Signal Separation Bin Yin Faculty of Electrical Engineering Eindhoven University of Technology P.O. Box513 5600 MB Eindhoven The Netherlands Storage Signal Processing Group Philips Research Laboratories P. O. Box WY-31 5656 AA Eindhoven The Netherlands Email bin.yin@philips.com Piet C. W. Sommen Faculty of Electrical Engineering Eindhoven University of Technology P.O. Box513 5600 MB Eindhoven The Netherlands Email p.c.w.sommen@tue.nl Peiyu He Faculty of Electrical Engineering Eindhoven University of Technology P.O. Box513 5600 MB Eindhoven The Netherlands University of Sichuan Chengdu 610064 China Email hepeiyu@hotmail.com Received 20 September 2002 and in revised form 26 May 2003 Blind signal separation can easily find its position in audio applications where mutually independent sources need to be separated from their microphone mixtures while both room acoustics and sources are unknown. However the conventional separation algorithms can hardly be implemented in real time due to the high computational complexity. The computational load is mainly caused by either direct or indirect estimation of thousands of acoustic parameters. Aiming at the complexity reduction in this paper the acoustic paths are investigated through an acoustic similarity index ASI . Then a new mixing model is proposed. With closely spaced microphones 5-10 cm apart the model relieves the computational load of the separation algorithm by reducing the number and length ofthe filters to be adjusted. To cope with real situations a blind audio signal separation algorithm BLASS is developed on the proposed model. BLASS only uses the second-order statistics SOS and performs efficiently in frequency domain. Keywords and phrases blind signal separation acoustic similarity noncausality. 1. INTRODUCTION In recent years blind signal separation BSS