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A coupled HMM for solving the permutation problem in frequency domain BSS

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conference contribution
posted on 04.02.2010, 17:20 by Saeid Sanei, Wenwu Wang, Jonathon Chambers
Permutation of the outputs at different frequency bins remains as a major problem in the convolutive blind source separation (BSS). In this work a coupled Hidden Markov model (CHMM) effectively exploits the psychoacoustic characteristics of signals to mitigate such permutation. A joint diagonalization algorithm for convolutive BSS, which incorporates a non-unitary penalty term within the crosspower spectrum-based cost function in the frequency domain, has been used. The proposed CHMM system couples a number of conventional HMMs, equivalent to the number of outputs, by making state transitions in each model dependent not only on its own previous state, but also on some aspects of the state of the other models. Using this method the permutation effect has been substantially reduced, and demonstrated using a number of simulation studies.



  • Mechanical, Electrical and Manufacturing Engineering


SANEI, S., WANG, W. and CHAMBERS, J.A., 2004. A coupled HMM for solving the permutation problem in frequency domain BSS. IN: Proceedings of 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '04), Montreal, Quebec, 17-21 May, Vol. 5, pp. 565-8.




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