Abstract
The problem of Blind Source Separation (BSS) of convolved acoustic signals is of great interest for many classes of applications such as in-car speech recognition, hands-free telephony or hearing devices. Due to the convolutive mixing process, the source separation is performed in the frequency domain, using Independent Component Analysis (ICA). However the quality of solution of the ICA-algorithms can be improved by applying time-frequency masking. In this paper we present a batch-algorithm for time-frequency masking using the time-frequency structure of separated signals. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Hoffmann, E., Kolossa, D., & Orglmeister, R. (2007). A batch algorithm for blind source separation of acoustic signals using ICA and time-frequency masking. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4666 LNCS, pp. 480–487). Springer Verlag. https://doi.org/10.1007/978-3-540-74494-8_60
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