Semi-blind source separation (SBSS) is a special case of the well-known blind source separation (BSS) when some partial knowledge of the source signals is available to the system. In particular, a batch adaptation in the frequency domain based on independent component analysis (ICA) can be effectively used to jointly perform source separation and multi-channel acoustic echo cancellation (MCAEC) through SBSS without double-talk detection. Many issues related to the implementation of an SBSS system are discussed in this paper. After a deep analysis of the structure of the SBSS adaptation, we propose a constrained batch-online implementation that stabilizes the convergence behavior even in the worst-case scenario of a single far-end talker along with the non-uniqueness condition on the far-end mixing system. Specifically, a matrix constraint is proposed to reduce the effect of the non-uniqueness problem caused by highly correlated far-end reference signals during MCAEC. Experimental results show that high echo cancellation can be achieved just as the misalignment remains relatively low without any pre-processing procedure to decorrelate the far-end signals even for the single far-end talker case.

Batch-Online Semi-Blind Source Separation Applied to Multi-Channel Acoustic Echo Cancellation

Nesta, Francesco;
2011-01-01

Abstract

Semi-blind source separation (SBSS) is a special case of the well-known blind source separation (BSS) when some partial knowledge of the source signals is available to the system. In particular, a batch adaptation in the frequency domain based on independent component analysis (ICA) can be effectively used to jointly perform source separation and multi-channel acoustic echo cancellation (MCAEC) through SBSS without double-talk detection. Many issues related to the implementation of an SBSS system are discussed in this paper. After a deep analysis of the structure of the SBSS adaptation, we propose a constrained batch-online implementation that stabilizes the convergence behavior even in the worst-case scenario of a single far-end talker along with the non-uniqueness condition on the far-end mixing system. Specifically, a matrix constraint is proposed to reduce the effect of the non-uniqueness problem caused by highly correlated far-end reference signals during MCAEC. Experimental results show that high echo cancellation can be achieved just as the misalignment remains relatively low without any pre-processing procedure to decorrelate the far-end signals even for the single far-end talker case.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/12019
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