Abstract
Blind Source Separation (BSS) techniques aim at recovering unobserved source signals from observed mixtures (typically, the outputs of an array of sensors). Practically all classical BSS techniques do not work properly under reverberant conditions and therefore, it still remains an open problem. In this sense, we propose in this document the use of synchronization of speech mixtures in order to improve the results of classical BSS techniques. Specifically, we have applied the synchronization of mixtures combined with one of the most well-known and robust BSS algorithms that works under non-reverberant conditions, the Degenerate Unmixing Estimation Technique (DUET). In the aim of synchronizing speech mixtures prior to the speech source separation, the suitability of working with seven Time Delay Estimation (TDE) techniques has been analyzed. Results show the feasibility of using synchronization since the results of DUET are improved and additionally, it has been observed what is the most useful TDE algorithm in this framework.
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Llerena, C., Gil-Pita, R., Álvarez, L., Rosa-Zurera, M. (2013). Synchronizing Speech Mixtures in Speech Separation Problems under Reverberant Conditions. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2013. Lecture Notes in Computer Science(), vol 7894. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38658-9_52
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DOI: https://doi.org/10.1007/978-3-642-38658-9_52
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