Keisuke Toyama

Using phase linearity in frequency-domain ICA to tackle the permutation problem

This paper describes a method for solving the permutation problem in the frequency-domain independent component analysis (FD-ICA) approach to blind source separation (BSS). FD-ICA is a well-known method for BSS of convolutive mixtures. However, FD-ICA has a source permutation problem, where estimated source components can become swapped at different frequencies. Many researchers have suggested methods to solve the source permutation problem including using correlation between adjacent frequencies and direction of arrival (DOA). We propose a modification to the DOA method, based on phase linearity of the FD-ICA de-mixing matrix, that can extend the range of frequencies over which the permutation problem can be resolved. Experiments indicate that our method can provide a better performance than the inter-frequency correlation method and the DOA method in real environments.