Overdetermined Blind Separation for Real Convolutive Mixtures of Speech Based on Multistage ICA Using Subarray Processing

Tsuyoki NISHIKAWA; Hiroshi ABE; Hiroshi SARUWATARI; Kiyohiro SHIKANO; Atsunobu KAMINUMA

Overdetermined Blind Separation for Real Convolutive Mixtures of Speech Based on Multistage ICA Using Subarray Processing

Tsuyoki NISHIKAWA, Hiroshi ABE, Hiroshi SARUWATARI, Kiyohiro SHIKANO, Atsunobu KAMINUMA

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We propose a new algorithm for overdetermined blind source separation (BSS) based on multistage independent component analysis (MSICA). To improve the separation performance, we have proposed MSICA in which frequency-domain ICA and time-domain ICA are cascaded. In the original MSICA, the specific mixing model, where the number of microphones is equal to that of sources, was assumed. However, additional microphones are required to achieve an improved separation performance under reverberant environments. This leads to alternative problems, e.g., a complication of the permutation problem. In order to solve them, we propose a new extended MSICA using subarray processing, where the number of microphones and that of sources are set to be the same in every subarray. The experimental results obtained under the real environment reveal that the separation performance of the proposed MSICA is improved as the number of microphones is increased.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E87-A No.8 pp.1924-1932

Publication Date: 2004/08/01

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Type of Manuscript: Special Section PAPER (Special Section on Digital Signal Processing)

Category: Speech/Acoustic Signal Processing

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Tsuyoki NISHIKAWA, Hiroshi ABE, Hiroshi SARUWATARI, Kiyohiro SHIKANO, Atsunobu KAMINUMA, "Overdetermined Blind Separation for Real Convolutive Mixtures of Speech Based on Multistage ICA Using Subarray Processing" in IEICE TRANSACTIONS on Fundamentals, vol. E87-A, no. 8, pp. 1924-1932, August 2004, doi: .
Abstract: We propose a new algorithm for overdetermined blind source separation (BSS) based on multistage independent component analysis (MSICA). To improve the separation performance, we have proposed MSICA in which frequency-domain ICA and time-domain ICA are cascaded. In the original MSICA, the specific mixing model, where the number of microphones is equal to that of sources, was assumed. However, additional microphones are required to achieve an improved separation performance under reverberant environments. This leads to alternative problems, e.g., a complication of the permutation problem. In order to solve them, we propose a new extended MSICA using subarray processing, where the number of microphones and that of sources are set to be the same in every subarray. The experimental results obtained under the real environment reveal that the separation performance of the proposed MSICA is improved as the number of microphones is increased.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/e87-a_8_1924/_p

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@ARTICLE{e87-a_8_1924,
author={Tsuyoki NISHIKAWA, Hiroshi ABE, Hiroshi SARUWATARI, Kiyohiro SHIKANO, Atsunobu KAMINUMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Overdetermined Blind Separation for Real Convolutive Mixtures of Speech Based on Multistage ICA Using Subarray Processing},
year={2004},
volume={E87-A},
number={8},
pages={1924-1932},
abstract={We propose a new algorithm for overdetermined blind source separation (BSS) based on multistage independent component analysis (MSICA). To improve the separation performance, we have proposed MSICA in which frequency-domain ICA and time-domain ICA are cascaded. In the original MSICA, the specific mixing model, where the number of microphones is equal to that of sources, was assumed. However, additional microphones are required to achieve an improved separation performance under reverberant environments. This leads to alternative problems, e.g., a complication of the permutation problem. In order to solve them, we propose a new extended MSICA using subarray processing, where the number of microphones and that of sources are set to be the same in every subarray. The experimental results obtained under the real environment reveal that the separation performance of the proposed MSICA is improved as the number of microphones is increased.},
keywords={},
doi={},
ISSN={},
month={August},}

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TY - JOUR
TI - Overdetermined Blind Separation for Real Convolutive Mixtures of Speech Based on Multistage ICA Using Subarray Processing
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1924
EP - 1932
AU - Tsuyoki NISHIKAWA
AU - Hiroshi ABE
AU - Hiroshi SARUWATARI
AU - Kiyohiro SHIKANO
AU - Atsunobu KAMINUMA
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E87-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2004
AB - We propose a new algorithm for overdetermined blind source separation (BSS) based on multistage independent component analysis (MSICA). To improve the separation performance, we have proposed MSICA in which frequency-domain ICA and time-domain ICA are cascaded. In the original MSICA, the specific mixing model, where the number of microphones is equal to that of sources, was assumed. However, additional microphones are required to achieve an improved separation performance under reverberant environments. This leads to alternative problems, e.g., a complication of the permutation problem. In order to solve them, we propose a new extended MSICA using subarray processing, where the number of microphones and that of sources are set to be the same in every subarray. The experimental results obtained under the real environment reveal that the separation performance of the proposed MSICA is improved as the number of microphones is increased.
ER -