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Signal Processing - Special issue on higher order statistics
A Course in Digital Signal Processing
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Subband-Based Blind Separation for Convolutive Mixtures of Speech
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Fast approximate joint diagonalization incorporating weight matrices
IEEE Transactions on Signal Processing
IEEE Transactions on Audio, Speech, and Language Processing
Performance measurement in blind audio source separation
IEEE Transactions on Audio, Speech, and Language Processing
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
The 2010 signal separation evaluation campaign (SiSEC2010): audio source separation
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
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T-ABCD is a time-domain method for blind linear separation of audio sources proposed by Koldovský and Tichavský (2008). The method produces short separating filters (5-40 taps) and works well with signals recorded at the sampling frequency of 8-16 kHz. In this paper, we propose a novel subband-based variant of T-ABCD, in which the input signals are decomposed into subbands using a tree-structured QMF filter bank. T-ABCD is then applied to each subband in parallel, and the separated subbands are re-ordered and synthesized to yield the final separated signals. The analysis filter of the filter bank is carefully designed to enable maximal decimation of signals without aliasing. Short filters applied within subbands then result in sufficiently long filters in fullband. Using a reasonable number of subbands, the method yields improved speed, stability and performance at an arbitrary sampling frequency.