The 2016 Signal Separation Evaluation CampaignReport as inadecuate

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1 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery 2 AUDIO LABS - International Audio Laboratories Erlangen 3 Gracenote, Media Technology Lab 4 Graduate University for Advanced Studies SOKENDAI 5 GIPSA-VIBS - VIBS GIPSA-DIS - Département Images et Signal 6 Université de Nagoya 7 The University of Tokyo 8 PRETA TIMC-IMAG - Techniques de l-Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications Grenoble

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.

Keywords : evaluation source separation

Author: Antoine Liutkus - Fabian-Robert Stöter - Zafar Rafii - Daichi Kitamura - Bertrand Rivet - Nobutaka Ito - Nobutaka Ono - Julie Fo



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