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A multistage approach for blind separation of convolutive speech mixtures

Jan, T, Wang, W and Wang, D (2009) A multistage approach for blind separation of convolutive speech mixtures In: ICASSP'09, 2009-04-19 - 2009-04-24, Taipei, Taiwan.

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In this paper, we propose a novel algorithm for the separation of convolutive speech mixtures using two-microphone recordings, based on the combination of independent component analysis (ICA) and ideal binary mask (IBM), together with a post-filtering process in the cepstral domain. Essentially, the proposed algorithm consists of three steps. First, a constrained convolutive ICA algorithm is applied to separate the source signals from two-microphone recordings. In the second step, we estimate the IBM by comparing the energy of corresponding time-frequency (T-F) units from the separated sources obtained with the convolutive ICA algorithm. The last step is to reduce musical noise caused typically by T-F masking using cepstral smoothing. The performance of the proposed approach is evaluated based on both reverberant mixtures generated using a simulated room model and real recordings. The proposed algorithm offers considerably higher efficiency, together with improved speech quality while producing similar separation performance as compared with a recent approach.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
Jan, T
Wang, W
Wang, D
Date : 26 May 2009
DOI : 10.1109/ICASSP.2009.4959933
Contributors :
Depositing User : Symplectic Elements
Date Deposited : 28 Mar 2017 14:43
Last Modified : 31 Oct 2017 14:37

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