SPEECH EXTRACTION BASED UPON A COMBINED SUBBAND INDEPENDENT COMPONENT ANALYSIS AND NEURAL MEMORY
Tetsuya Hoya, Allan Kardec Barros, Tomasz M. Rutkowski, Andrzej S Cichocki · 2003
This paper presents a novel approach for speech extraction by a combined subband independent component analysis and neural memory. In the approach, probabilistic neural networks followed by the subband independent component analysis processing units are used for the neural memory to identify firstly the speaker and then compensate for the `side-effects', i.e., the scaling and the permutation disorder, both of which are particularly problematic for subband blind extraction. Simulation study shows that the combined scheme can effectively extract the speech signal of interest from the instantaneous/delayed mixtures, in comparison with the conventional subband/fullband approaches.