The 2015 Signal Separation Evaluation Campaign

  • Nobutaka OnoEmail author
  • Zafar Rafii
  • Daichi Kitamura
  • Nobutaka Ito
  • Antoine Liutkus
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9237)


In this paper, we report the 2015 community-based Signal Separation Evaluation Campaign (SiSEC 2015). This SiSEC consists of four speech and music datasets including two new datasets: “Professionally produced music recordings” and “Asynchronous recordings of speech mixtures”. Focusing on them, we overview the campaign specifications such as the tasks, datasets and evaluation criteria. We also summarize the performance of the submitted systems.


Source Separation Deep Neural Network Robust Principal Component Analysis Permutation Problem Glottal Closure Instant 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We would like to thank Dr. Shigeki Miyabe for providing the new ASY dataset, and Mike Senior for giving us the permission to use the MSD database for creating the MSD100 corpus.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Nobutaka Ono
    • 1
    Email author
  • Zafar Rafii
    • 2
  • Daichi Kitamura
    • 3
  • Nobutaka Ito
    • 4
  • Antoine Liutkus
    • 5
  1. 1.National Institute of InformaticsTokyoJapan
  2. 2.Media Technology LabGracenoteEmeryvilleUSA
  3. 3.SOKENDAI (The Graduate University for Advanced Studies)HayamaJapan
  4. 4.NTT Communication Science LaboratoriesNTT CorporationKyotoJapan
  5. 5.INRIAVillers-lès-NancyFrance

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