A Fixed-Point ICA Algorithm for Convoluted Speech Signal Separation


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Please use this identifier to cite or link to this item: http://hdl.handle.net/10061/8010

Title:	A Fixed-Point ICA Algorithm for Convoluted Speech Signal Separation
Authors:	Rajkishore Prasad Hiroshi Saruwatari Akinobu Lee Kiyohiro Shikano
Issue Date:	Apr-2003
Start page:	579
End page:	584
Abstract:	This paper describes a fixed-point independent component analysis (ICA) algorithm in combination with the null beamforming technique to sieve out speech signals from their convoluted mixture observed using a linear microphone array. The fixed-point algorithm shows fast convergence to the solution, however it is highly sensitive to the initial value from which iteration starts. A good initial value leads to faster convergence and yields better results. We propose the use of a null beamformer-based initial value for iteration and explore its effects on separation performance under different acoustic conditions by examining the noise reduction rate (NRR) and convergence speed. The result of the simulation confirms the efficacy and accuracy of the proposed algorithm.
Description:	ICA2003: 4th International Symposium on Independent Component Analysis and Blind Signal Separation, April 1-4, 2003, Nara, Japan.
URI:	http://hdl.handle.net/10061/8010
Text Version:	Publisher
Appears in Collections:	情報科学研究科 / Graduate School of Information Science

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