Abstract
In this paper, we report the results of the 2016 communitybased Signal Separation Evaluation Campaign (SiSEC 2016). This edition comprises four tasks. Three focus on the separation of speech and music audio recordings, while one concerns biomedical signals. We summarize these tasks and the performance of the submitted systems, as well as provide a small discussion concerning future trends of SiSEC.
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CITATION STYLE
Liutkus, A., Stöter, F. R., Rafii, Z., Kitamura, D., Rivet, B., Ito, N., … Fontecave, J. (2017). The 2016 signal separation evaluation campaign. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10169 LNCS, pp. 323–332). Springer Verlag. https://doi.org/10.1007/978-3-319-53547-0_31
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