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Title: Speech Enhancement in Car Environment Using Blind Source Separation
Authors: Hiroshi Saruwatari
Katsuyuki Sawai
Akinobu Lee
Kiyohiro Shikano
Atsunobu Kaminuma
Masao Sakata
Issue Date: Sep-2002
Start page: 1781
End page: 1784
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: ICSLP2002: the 7th International Conference on Spoken Language Processing , September 16-20, 2002, Denver, Colorado, USA.
Rights: Copyright 2002 ISCA
Text Version: Publisher
Appears in Collections:情報科学研究科 / Graduate School of Information Science

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