Abstract
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.
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Cermak, J., Smekal, Z. (2009). Underdetermined Blind Source Separation Using Linear Separation System. In: Esposito, A., Hussain, A., Marinaro, M., Martone, R. (eds) Multimodal Signals: Cognitive and Algorithmic Issues. Lecture Notes in Computer Science(), vol 5398. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00525-1_30
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DOI: https://doi.org/10.1007/978-3-642-00525-1_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00524-4
Online ISBN: 978-3-642-00525-1
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