Abstract
In this work, we have proposed an approach which combines two source separation techniques, convolutive blind source separation (BSS) exploiting the second-order non-stationary signals and binary time-frequency masking, together with a cepstral smoothing post-processing. The latter consists in smoothing of the estimated binary masks from the outputs of BSS algorithm in cepstral domain. The idea behind employing a cepstral smoothing of spectral masks is to improve the interference suppression and to reduce musical noise typically produced by time-frequency masking. Experimental results and the evaluation measurement prove the performance of proposed convolutive blind speech separation system.
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Missaoui, I., Lachiri, Z. (2011). Cepstral Smoothing for Convolutive Blind Speech Separation. In: Das, V.V., Thankachan, N. (eds) Computational Intelligence and Information Technology. CIIT 2011. Communications in Computer and Information Science, vol 250. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25734-6_43
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DOI: https://doi.org/10.1007/978-3-642-25734-6_43
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