Dataset Open Access

Bach10 Separation SMC2017

Marius Miron


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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.344499", 
  "title": "Bach10 Separation SMC2017", 
  "issued": {
    "date-parts": [
      [
        2017, 
        2, 
        28
      ]
    ]
  }, 
  "abstract": "<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 (https://zenodo.org/record/321361#.WLW40t-i7J8), 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>\nhttp://music.cs.northwestern.edu/data/Bach10.html</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>", 
  "author": [
    {
      "family": "Marius Miron"
    }
  ], 
  "type": "dataset", 
  "id": "344499"
}
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