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An Acoustic Echo Canceller for Stereo Using Blind Signal Separation

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초록

This paper is on a stereo acoustic echo canceller with the blind signal separation. The convergence speed of the stereo acoustic echo canceller is deteriorated due to mixing two residual signals in the update signal of each echo canceller. To solve this problem, we are to use the blind signal separation(BSS) method separating the mixed signals. The blind signal separation method can extracts the source signals by means of the iterative computations with two input signals. We had verified performances of the proposed acoustic echo canceller for stereo through simulations. The results of simulations show that the acoustic echo canceller for stereo using this algorithm operates stably without divergence in the normal state. And, when the speech signals were inputted, this echo canceller achieved about 3dB higher ERLE in the case of using the BSS algorithm than the case of not using the BSS algorithm. But this echo canceller didn’t get good performances in the case of inputting the white noises as stereo signals.

Abstract

This paper is on a stereo acoustic echo canceller with the blind signal separation. The convergence speed of the stereo acoustic echo canceller is deteriorated due to mixing two residual signals in the update signal of each echo canceller. To solve this problem, we are to use the blind signal separation(BSS) method separating the mixed signals. The blind signal separation method can extracts the source signals by means of the iterative computations with two input signals. We had verified performances of the proposed acoustic echo canceller for stereo through simulations. The results of simulations show that the acoustic echo canceller for stereo using this algorithm operates stably without divergence in the normal state. And, when the speech signals were inputted, this echo canceller achieved about 3dB higher ERLE in the case of using the BSS algorithm than the case of not using the BSS algorithm. But this echo canceller didn’t get good performances in the case of inputting the white noises as stereo signals.

참고문헌 (8)

  1. J. Benesty, "Adaptive filtering algorithm for stereophonic acoustic echo cancelation", Proc. of Int. Conf. on Acoustic, Speech, and Signal Processing, pp.3099~3102 (1995)
  2. K. Murano, "Echo cancellation and applications", IEEE Comm. Magazine, pp.49~55 (1990)
  3. D. T. Pham, "Separation of a mixture of independent sources through a maximum likelyhood approach", Signal Processing VI: Theories and Applications, pp.771~774 (1992)
  4. P. Comon, "Independent component analysis, A new concept", Signal Processing, 36, pp.287~314 (1994)
  5. H. Saruwatari, "Blind Source Separation for Speech Based on Fast Convergence Algorithm with ICA and Beamforming", Proceedings of the Eurospeech 2001, pp.2603~2606 (2001)
  6. Bell A. J, "An Information Maximization Approach to Blind Separation and Blind Deconvolution", Neural Computation, 7, pp.1129~1159 (1995)
  7. Kari Torkkola, "Blind Separation of Convolved Sources Based on Information Maximization", Neural Networks for Signal Processing, IEEE Signal Processing Society Workshop (1996)
  8. D. W. E. Schobben, P., "Sommen, A frequency domain blind signal separation method based on decorrelation", IEEE Trans. Signal Process, 50(8), pp.1855~1865 (2002)

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