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Batch and Adaptive PARAFAC-Based Blind Separation of Convolutive Speech Mixtures
2010
IEEE Transactions on Audio, Speech, and Language Processing
We present a frequency-domain technique based on PARAllel FACtor (PARAFAC) analysis that performs multichannel blind source separation (BSS) of convolutive speech mixtures. PARAFAC algorithms are combined with a dimensionality reduction step to significantly reduce computational complexity. The identifiability potential of PARAFAC is exploited to derive a BSS algorithm for the under-determined case (more speakers than microphones), combining PARAFAC analysis with time-varying Capon beamforming.
doi:10.1109/tasl.2009.2031694
fatcat:bn4b6bnnvfa6doyrr67rrai3si