Dataset Open Access

Bach10 Separation SMC2017

Marius Miron


JSON-LD (schema.org) Export

{
  "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 (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>", 
  "license": "http://creativecommons.org/licenses/by-nc/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Universitat Pompeu Fabra, Barcelona", 
      "@type": "Person", 
      "name": "Marius Miron"
    }
  ], 
  "url": "https://zenodo.org/record/344499", 
  "datePublished": "2017-02-28", 
  "keywords": [
    "source separation", 
    "classical music", 
    "neural networks"
  ], 
  "@context": "https://schema.org/", 
  "distribution": [
    {
      "contentUrl": "https://zenodo.org/api/files/143b437e-4a0f-4244-9828-9495f113c8dc/Bach10 Separation SMC2017.tar.gz", 
      "@type": "DataDownload", 
      "fileFormat": "gz"
    }
  ], 
  "identifier": "https://doi.org/10.5281/zenodo.344499", 
  "@id": "https://doi.org/10.5281/zenodo.344499", 
  "@type": "Dataset", 
  "name": "Bach10 Separation SMC2017"
}
108
20
views
downloads
All versions This version
Views 108109
Downloads 2020
Data volume 22.3 GB22.3 GB
Unique views 9899
Unique downloads 1818

Share

Cite as