Solving the Permutation Problem Using Phase Linearity and Frequency Correlation

This paper describes a method for solving the permutation problem in blind source separation (BSS) by frequencydomain independent component analysis (FD-ICA). FDICA 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. In this paper, we discuss a new method for solving the permutation problem, based on the linearity of the phase response of the FD-ICA de-mixing matrix, and a combination method of the proposed phase linearity method and the inter-frequency correlation method. Initial results indicate that our methods can provide an almost perfect solution to the permutation problem in an anechoic environment, and better performance than the inter-frequency correlation method alone in an echoic environment.