Independent component analysis: algorithms and applications
Neural Networks
A system for information retrieval from large records of czech spoken data
TSD'06 Proceedings of the 9th international conference on Text, Speech and Dialogue
Blind separation of speech mixtures via time-frequency masking
IEEE Transactions on Signal Processing
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In automatic speech and speech emotion recognition, a good quality of input speech signal is often required. The hit rate of recognizers is lowered by degradation of speech quality due to noise. Blind source separation can be used to enhance the speech signal as a part of preprocessing techniques. This paper presents a multi channel linear blind source separation method that can be applied even in underdetermined case i.e. when the number of source signals is higher than the number of sensors. Experiments have shown that our system outperforms conventional time-frequency binary masking in both determined and underdetermined cases and significantly increases the hit rate of speech recognizers.