The 2016 Signal Separation Evaluation Campaign

Antoine Liutkus 1 Fabian Robert-Stöter 2 Zafar Rafii 3 Daichi Kitamura 4 Bertrand Rivet 5 Nobutaka Ito 6 Nobutaka Ono 7 Julie Fontecave 8
1 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
GIPSA-DIS - Département Images et Signal, GIPSA-PSD - GIPSA Pôle Sciences des Données
8 TIMC-IMAG-PRETA - Physiologie cardio-Respiratoire Expérimentale Théorique et Appliquée
TIMC-IMAG - Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble - UMR 5525
Abstract : In this paper, we report the results of the 2016 community-based 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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Conference papers
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Submitted on : Tuesday, February 21, 2017 - 2:54:06 PM
Last modification on : Friday, January 10, 2020 - 11:42:08 AM
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Antoine Liutkus, Fabian Robert-Stöter, Zafar Rafii, Daichi Kitamura, Bertrand Rivet, et al.. The 2016 Signal Separation Evaluation Campaign. 13th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2017), Feb 2017, Grenoble, France. pp.323 - 332, ⟨10.1007/978-3-319-53547-0_31⟩. ⟨hal-01472932⟩



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