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Title: Speech Enhancement and Recognition in Car Environment using Blind Source Separation and Subband Elimination Processing
Authors: Hiroshi Saruwatari
Katsuyuki Sawai
Akinobu Lee
Kiyohiro Shikano
Atsunobu Kaminuma
Masao Sakata
Issue Date: Apr-2003
Start page: 367
End page: 372
Abstract: We propose a new algorithm for blind source separation (BSS), in which independent component analysis (ICA) and beamforming are combined to resolve the low-convergence problem through optimization in ICA. The proposed method consists of the following four parts: (1) frequency-domain ICA with direction-of-arrival (DOA) estimation, ( 2) null beamforming based on the estimated DOA, (3) diversity of (1) and (2) in both iteration and frequency domain, and (4) subband elimination (SBE) based on the independence among the separated signals. The temporal alternation between ICA and beamforming can realize fast-and high-convergence optimization. Also SBE enforcedly eliminates the subband components in which the separation could not be performed well. The experiment in a real car environment reveals that the proposed method can improve the qualities of the separated speech and word recognition rates for both directional and diffusive noises.
Description: ICA2003: 4th International Symposium on Independent Component Analysis and Blind Signal Separation, April 1-4, 2003, Nara, Japan.
Text Version: Publisher
Appears in Collections:情報科学研究科 / Graduate School of Information Science

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