One of the most important problems in frequency domain blind source separation is the inconsistency across frequency in the permutation of the source estimates. In this paper we present a new algorithm that simultaneously diagonalizes the intra-frequency and the inter-frequency correlation matrices of the source estimates. Experimental results, using speech signals, reveal that the algorithm achieves a highly improved alignment of the permutations between neighbor frequency bins.
Cite as: Robledo-Arnuncio, E., Juang, B.-H. (2005) Using inter-frequency decorrelation to reduce the permutation inconsistency problem in blind source separation. Proc. Interspeech 2005, 2357-2360, doi: 10.21437/Interspeech.2005-750
@inproceedings{robledoarnuncio05_interspeech,
author={Enrique Robledo-Arnuncio and Biing-Hwang Juang},
title={{Using inter-frequency decorrelation to reduce the permutation inconsistency problem in blind source separation}},
year=2005,
booktitle={Proc. Interspeech 2005},
pages={2357--2360},
doi={10.21437/Interspeech.2005-750}
}