DocumentCode :
3342794
Title :
Lattice-ladder decorrelation filters developed for co-channel speech separation
Author :
Yen, Kuan-Chieh ; Zhao, Yunxin
Author_Institution :
Dept. of CECS, Missouri Univ., Columbia, MO, USA
Volume :
1
fYear :
2001
fDate :
2001
Firstpage :
637
Abstract :
The previously proposed lattice-ladder adaptive decorrelation filtering (LL-ADF) algorithm (Ken and Zhao 1999) is further studied and improved in this work, with the aim of developing a more efficient co-channel speech separation system. The effect of the joint linear predictions is first analyzed and the conversions between the lattice coefficients and the prediction and filter vectors are formulated. The implementation issues on the estimation of lattice coefficients are then discussed and the adaptation equations are further refined. Experimental results demonstrate the effectiveness of the algorithm in reducing cross-interference between co-channel speech sources as well as the significant performance improvement over the previous direct-form ADF algorithm. A simplified LL-ADF is also proposed as a compromise between computational cost and system performance
Keywords :
FIR filters; adaptive filters; decorrelation; lattice filters; parameter estimation; prediction theory; speech enhancement; LL-ADF algorithm; adaptation equations; co-channel speech separation; computational cost; conversions; cross-interference; filter vectors; joint linear predictions; lattice coefficients; lattice-ladder adaptive decorrelation filtering; prediction vectors; system performance; Adaptive filters; Computational efficiency; Decorrelation; Equations; Filtering algorithms; Lattices; Nonlinear filters; Speech; System performance; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
Conference_Location :
Salt Lake City, UT
ISSN :
1520-6149
Print_ISBN :
0-7803-7041-4
Type :
conf
DOI :
10.1109/ICASSP.2001.940912
Filename :
940912
Link To Document :
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