PROJECT TITLE :

Reducing permutation error in subband-based convolutive blind separation

ABSTRACT:

Subband-based blind source separation has great potential in solving the complicated convolutive mixing problem. However, its performance is largely affected by the permutation ambiguity problem during the synthesis stage. Researchers have suggested methods to correct the permutation by exploiting the correlation information between adjacent frequencies/subbands. An improved solution to this permutation problem is proposed based on a novel filter banks design method, which is based on a model that includes inter-subband correlation as part of the optimisation criterion. Simulation results show that a better subband permutation alignment result has been achieved, leading to improved separation performance.