Abstract
For most of the blind separation methods of convolutive mixtures, the parameters of unmixing filter are derived in frequency domain. This leads to a seldom mentioned but important problem that generally the independence assumption between source signals collapses in frequency domain because of the inadequate samples. There exists correlation at each frequency bin. Sometimes it is too high to be neglected and consequently degrades the performance of all the BSS methods in various degrees. In this paper, we propose a recursive algorithm for lowering the unfavorable effect from the correlation, and combine it with the TDD-based blind separation method proposed by S. Ikeda and N. Murata. The bin mixtures are separated into the components of the sources as practical instead of the independent bins as achieved by the conventional method. The signal-to-noise ratio is greatly increased at certain bins, which results in a much better separation.
