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Blind convolutive separation method for speech signals via joint block diagonalization (2010 No. 1)
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ZHANG Hua1  FENG Dazheng1  PANG Jiyong2

(1 National Lab. of Radar Signal Process, Xidian Univ.  Xi'an 710071)

(2 State Key Lab. of Integrated Service Networks, Xidian Univ.  Xi'an  710071)

Received Sept. 5, 2008

Revised Dec. 18, 2008

Abstract A blind speech source separation method for the overdetermined convolutive mixture model in time-domain is proposed via joint block-diagonalization based on the mutual-independence and short-time stationary properties of the speech signals. Taking the sum of the F-norms of all off-diagonal sub-matrices as criterion, a novel joint block-diagonalization method is proposed to estimate the whole mixture matrix through minimizing a sequence of quadratic sub-functions corresponding to mixture sub-matrices. Both theoretical analysis and simulations show that the proposed method has much lower complexity and faster convergence speed that the classical Jacobi-like method with no performance loss. In addition, there are almost no obvious impacts of the channel order and initialization values on the convergence speed.   

PACS numbers: 43.60

 
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