IEICE TRANSACTIONS on Fundamentals
Blind Separation and Deconvolution for Convolutive Mixture of Speech Combining SIMO-Model-Based ICA and Multichannel Inverse Filtering
Summary :
We propose a new two-stage blind separation and deconvolution strategy for multiple-input multiple-output (MIMO)-FIR systems driven by colored sound sources, in which single-input multiple-output (SIMO)-model-based ICA (SIMO-ICA) and blind multichannel inverse filtering are combined. SIMO-ICA can separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. After the separation by the SIMO-ICA, a blind deconvolution technique for the SIMO model can be applied even when each source signal is temporally correlated and the mixing system has a nonminimum phase property. The simulation results reveal that the proposed algorithm can successfully achieve separation and deconvolution of a convolutive mixture of speech, and outperforms a number of conventional ICA-based BSD methods.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E88-A No.9 pp.2387-2400
- Publication Date
- 2005/09/01
- Publicized
- Online ISSN
- DOI
- 10.1093/ietfec/e88-a.9.2387
- Type of Manuscript
- PAPER
- Category
- Engineering Acoustics
Authors
Keyword
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Hiroshi SARUWATARI, Hiroaki YAMAJO, Tomoya TAKATANI, Tsuyoki NISHIKAWA, Kiyohiro SHIKANO, "Blind Separation and Deconvolution for Convolutive Mixture of Speech Combining SIMO-Model-Based ICA and Multichannel Inverse Filtering" in IEICE TRANSACTIONS on Fundamentals,
vol. E88-A, no. 9, pp. 2387-2400, September 2005, doi: 10.1093/ietfec/e88-a.9.2387.
Abstract: We propose a new two-stage blind separation and deconvolution strategy for multiple-input multiple-output (MIMO)-FIR systems driven by colored sound sources, in which single-input multiple-output (SIMO)-model-based ICA (SIMO-ICA) and blind multichannel inverse filtering are combined. SIMO-ICA can separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. After the separation by the SIMO-ICA, a blind deconvolution technique for the SIMO model can be applied even when each source signal is temporally correlated and the mixing system has a nonminimum phase property. The simulation results reveal that the proposed algorithm can successfully achieve separation and deconvolution of a convolutive mixture of speech, and outperforms a number of conventional ICA-based BSD methods.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e88-a.9.2387/_p
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@ARTICLE{e88-a_9_2387,
author={Hiroshi SARUWATARI, Hiroaki YAMAJO, Tomoya TAKATANI, Tsuyoki NISHIKAWA, Kiyohiro SHIKANO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Blind Separation and Deconvolution for Convolutive Mixture of Speech Combining SIMO-Model-Based ICA and Multichannel Inverse Filtering},
year={2005},
volume={E88-A},
number={9},
pages={2387-2400},
abstract={We propose a new two-stage blind separation and deconvolution strategy for multiple-input multiple-output (MIMO)-FIR systems driven by colored sound sources, in which single-input multiple-output (SIMO)-model-based ICA (SIMO-ICA) and blind multichannel inverse filtering are combined. SIMO-ICA can separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. After the separation by the SIMO-ICA, a blind deconvolution technique for the SIMO model can be applied even when each source signal is temporally correlated and the mixing system has a nonminimum phase property. The simulation results reveal that the proposed algorithm can successfully achieve separation and deconvolution of a convolutive mixture of speech, and outperforms a number of conventional ICA-based BSD methods.},
keywords={},
doi={10.1093/ietfec/e88-a.9.2387},
ISSN={},
month={September},}
Copy
TY - JOUR
TI - Blind Separation and Deconvolution for Convolutive Mixture of Speech Combining SIMO-Model-Based ICA and Multichannel Inverse Filtering
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2387
EP - 2400
AU - Hiroshi SARUWATARI
AU - Hiroaki YAMAJO
AU - Tomoya TAKATANI
AU - Tsuyoki NISHIKAWA
AU - Kiyohiro SHIKANO
PY - 2005
DO - 10.1093/ietfec/e88-a.9.2387
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E88-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2005
AB - We propose a new two-stage blind separation and deconvolution strategy for multiple-input multiple-output (MIMO)-FIR systems driven by colored sound sources, in which single-input multiple-output (SIMO)-model-based ICA (SIMO-ICA) and blind multichannel inverse filtering are combined. SIMO-ICA can separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. After the separation by the SIMO-ICA, a blind deconvolution technique for the SIMO model can be applied even when each source signal is temporally correlated and the mixing system has a nonminimum phase property. The simulation results reveal that the proposed algorithm can successfully achieve separation and deconvolution of a convolutive mixture of speech, and outperforms a number of conventional ICA-based BSD methods.
ER -
English
