Blind Source Separation of Convolutive Mixtures of Speech in Frequency Domain(<Special Section>Multi-channel Acoustic Signal Processing)
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概要
- 論文の詳細を見る
This paper overviews a total solution for frequency-domain blind source separation (BSS) of convolutive mixtures of audio signals, especially speech. Frequency-domain BSS performs independent component analysis (ICA) in each frequency bin, and this is more efficient than time-domain BSS. We describe a sophisticated total solution for frequency-domain BSS, including permutation, scaling, circularity, and complex activation function solutions. Experimental results of 2×2, 3×3, 4×4, 6×8, and 2×2 (moving sources), (#sources×#microphones) in a room are promising.
- 社団法人電子情報通信学会の論文
- 2005-07-01
著者
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Sawada Hiroshi
Ntt Communication Science Laboratories Ntt Corporation
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Makino Shoji
NTT Communication Science Laboratories
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MUKAI Ryo
NTT Communication Science Laboratories
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Makino Shoji
Ntt Communication Science Laboratories Ntt Corporation
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Makino S
Ntt Communication Sci. Lab. Kyoto Jpn
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Mukai Ryo
Ntt Communication Science Laboratories Ntt Corporation
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ARAKI Shoko
NTT Communication Science Laboratories, NTT Corporation
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Araki Shoko
Ntt Communication Science Laboratories Ntt Corporation
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Sawada Hiroshi
Ntt Communication Science Laboratories
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- FOREWORD
- Subband-Based Blind Separation for Convolutive Mixtures of Speech(Engineering Acoustics)
- Estimating the number of sources using independent component analysis
- Blind Source Separation of Convolutive Mixtures of Speech in Frequency Domain(Multi-channel Acoustic Signal Processing)
- Blind Source Separation for Moving Speech Signals Using Blockwise ICA and Residual Crosstalk Subtraction(Speech/Acoustic Signal Processing)(Digital Signal Processing)
- Convolutive blind source separation for more than two sources in the frequency domain
- Evaluation of separation and dereverberation performance in frequency domain blind source separation
- Underdetermined Blind Separation of Convolutive Mixtures of Speech Using Time-Frequency Mask and Mixing Matrix Estimation(Blind Source Separation, Multi-channel Acoustic Signal Processing)
- Sparse source separation based on simultaneous clustering of source locational and spectral features
- Stereophonic acoustic echo cancellation : An overview and recent solutions
- Polar Coordinate Based Nonlinear Function for Frequency-Domain Blind Source Separation