Improved Method of Blind Speech Separation with Low Computational Complexity

A blind speech separation method with low computational complexity is proposed. This method consists of a combination of independent component analysis with frequency band selection, and a frame-wise spectral soft mask method based on an interchannel power ratio of tentative separated signals in the...

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Bibliographic Details
Published in:Advances in acoustics and vibration 2011-01, Vol.2011 (1)
Main Authors: Kondo, Kazunobu, Takahashi, Yu, Hashimoto, Seiichi, Saruwatari, Hiroshi, Nishino, Takanori, Takeda, Kazuya
Format: Article
Language:English
Subjects:
Methods
Multivariate analysis
Signal processing
Technology application
Transfer functions
Voice recognition
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Summary:A blind speech separation method with low computational complexity is proposed. This method consists of a combination of independent component analysis with frequency band selection, and a frame-wise spectral soft mask method based on an interchannel power ratio of tentative separated signals in the frequency domain. The soft mask cancels the transfer function between sources and separated signals. A theoretical analysis of selection criteria and the soft mask is given. Performance and effectiveness are evaluated via source separation simulations and a computational estimate, and experimental results show the significantly improved performance of the proposed method. The segmental signal-to-noise ratio achieves 7 [dB] and 3 [dB], and the cepstral distortion achieves 1 [dB] and 2.5 [dB], in anechoic and reverberant conditions, respectively. Moreover, computational complexity is reduced by more than 80% compared with unmodified FDICA.
ISSN:1687-6261
1687-627X
1687-6261
DOI:10.1155/2011/765429