On-line Blind Source Separation of Non-Stationary Signals

|We have shown previously that non-stationary signals recorded in a static multi-path environment can often be recovered by simultaneously decorrelating varying second order statistics. As typical sources are often moving, however, the multi-path channel is not static. We present here an on-line gradient algorithm with adaptive step size in the frequency domain based on second derivatives, which we refer to as multiple adaptive decorrelation (MAD). We compared the separation performance of the proposed algorithm to its o -line counterpart and to another decorrelation based on-line algorithm.

[1]  L. Parra,et al.  Convolutive blind source separation based on multiple decorrelation , 1998, Neural Networks for Signal Processing VIII. Proceedings of the 1998 IEEE Signal Processing Society Workshop (Cat. No.98TH8378).

[2]  Russell H. Lambert,et al.  Blind separation of multiple speakers in a multipath environment , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[3]  Hareo Hamada,et al.  Inverse filter design and equalization zones in multichannel sound reproduction , 1995, IEEE Trans. Speech Audio Process..

[4]  Jose C. Principe,et al.  Simultaneous Diagonalization in the Frequency Domain (SDIF) for Source Separation , 2000 .

[5]  Henrik Sahlin,et al.  Separation of real-world signals , 1998, Signal Process..

[6]  Meir Feder,et al.  Multi-channel signal separation by decorrelation , 1993, IEEE Trans. Speech Audio Process..

[7]  Christian Jutten,et al.  Blind source separation for convolutive mixtures , 1995, Signal Process..

[8]  P. Peterson.  Simulating the response of multiple microphones to a single acoustic source in a reverberant room. , 1986, The Journal of the Acoustical Society of America.

[9]  Yunxin Zhao,et al.  Improvements on co-channel speech separation using ADF: low complexity, fast convergence, and generalization , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[10]  Yunxin Zhao,et al.  Adaptive co-channel speech separation and recognition , 1999, IEEE Trans. Speech Audio Process..

[11]  Dirk Van Compernolle,et al.  Signal separation in a symmetric adaptive noise canceler by output decorrelation , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[12]  S.C. Douglas,et al.  Multichannel blind deconvolution and equalization using the natural gradient , 1997, First IEEE Signal Processing Workshop on Signal Processing Advances in Wireless Communications.

[13]  Georgios B. Giannakis,et al.  Multichannel blind signal separation and reconstruction , 1997, IEEE Trans. Speech Audio Process..

[14]  Noboru Ohnishi,et al.  A method of blind separation for convolved non-stationary signals , 1998, Neurocomputing.

[15]  Paris Smaragdis,et al.  Blind separation of convolved mixtures in the frequency domain , 1998, Neurocomputing.

[16]  Andreas Ziehe,et al.  An approach to blind source separation based on temporal structure of speech signals , 2001, Neurocomputing.

[17]  B. A. D. H. Brandwood.  A complex gradient operator and its applica-tion in adaptive array theory , 1983 .

[18]  Ehud Weinstein,et al.  Multichannel signal separation: methods and analysis , 1996, IEEE Trans. Signal Process..

[19]  Sergio Cruces,et al.  A Gauss-Newton method for blind source separation of convolutive mixtures , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[20]  Jean-Louis Lacoume,et al.  Blind separation of wide-band sources in the frequency domain , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[21]  Dirk Van Compernolle,et al.  Signal separation by symmetric adaptive decorrelation: stability, convergence, and uniqueness , 1995, IEEE Trans. Signal Process..

[22]  Te-Won Lee,et al.  Blind Separation of Delayed and Convolved Sources , 1996, NIPS.

[23]  Shun-ichi Amari,et al.  Novel On-Line Adaptive Learning Algorithms for Blind Deconvolution Using the Natural Gradient Approach , 1997 .