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Bach10 Separation SMC2017

Marius Miron

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  "description": "<p>The Bach10 Separation SMC2017 dataset is derived from the Bach10 dataset, which contains ten pieces of Bach chorales along the scores.<br>\nWe separate the audio files in the original dataset and in the dataset we synthesized with Sibelius (, using the approaches presented in this paper:<br>\nMarius Miron, Jordi Janer, Emilia Gomez, \"Generating data to train convolutional neural networks for low latency classical music source separation\", Sound and Music Computing Conference 2017</p>\n\n<p>The dataset contains the separated audio files along the computed measures which give the quality of separation: SDR, SIR, SAR, computed with BSS Eval 3.0.\u00a0</p>\n\n<p>For the intellectual rights and the distribution policy of the original dataset check the Bach10 dataset page:<br>\n</p>\n\n<p>The files in Bach10 Separation SMC2017 dataset are offered free of charge for non-commercial use only. You can not redistribute them nor modify them.\u00a0</p>\n\n<p>This dataset is created by Marius Miron, Music Technology Group - Universitat Pompeu Fabra (Barcelona). This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 Unported License.</p>", 
  "license": "", 
  "creator": [
      "affiliation": "Universitat Pompeu Fabra, Barcelona", 
      "@type": "Person", 
      "name": "Marius Miron"
  "url": "", 
  "datePublished": "2017-02-28", 
  "keywords": [
    "source separation", 
    "classical music", 
    "neural networks"
  "@context": "", 
  "distribution": [
      "contentUrl": " Separation SMC2017.tar.gz", 
      "encodingFormat": "gz", 
      "@type": "DataDownload"
  "identifier": "", 
  "@id": "", 
  "@type": "Dataset", 
  "name": "Bach10 Separation SMC2017"
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