An Approach to Blind Source Separation of Speech Signals
In this paper we introduce a new technique for blind source separation of speech signals. We focused on the temporal structure of signals which is not always the case in other major approaches. The idea is to apply the decorrelation method proposed by Molgedey and Schuster in time-frequency domain. We show some results of experiments with artificial data and speech data recorded in the real environment. Our algorithm needs considerably straightforward calculation and includes only a few parameters to be tuned.
Unable to display preview. Download preview PDF.
- T.-W. Lee, A. Ziehe, R. Orglmeister, and T. Sejnowski. Combining time-delayed decorrelation and ICA: towards solving the cocktail party problem. In Proceedings of ICASSP’98, 1998.Google Scholar
- P. Smaragdis. Blind separation of convolved mixtures in the frequency domain. In International Workshop on Independence & Artificial Neural Networks, University of La Laguna, Tenerife, Spain, 1998.Google Scholar
- A. Ziehe. Statistische verfahren zur signalquellentrennung. Master’s thesis, Humboldt Universität, Berlin, 1998. (in German).Google Scholar