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MUSDB18-HQ - an uncompressed version of MUSDB18

Rafii, Zafar; Liutkus, Antoine; Stöter, Fabian-Robert; Mimilakis, Stylianos Ioannis; Bittner, Rachel


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{
  "description": "<p>MUSDB18-HQ is the uncompressed version of the MUSDB18 dataset. It consists of a total of 150 full-track songs of different styles and includes both the stereo mixtures and the original sources, divided between a training subset and a test subset.</p>\n\n<p>Its purpose is to serve as a reference database for the design and the evaluation of source separation algorithms. The objective of such signal processing methods is to estimate one or more sources from a set of mixtures, e.g. for karaoke applications. It has been used as the official dataset in the professionally-produced music recordings task for SiSEC 2018, which is the international campaign for the evaluation of source separation algorithms.</p>\n\n<p><em>musdb18-hq</em> contains two folders, a folder with a training set: &ldquo;train&rdquo;, composed of 100 songs, and a folder with a test set: &ldquo;test&rdquo;, composed of 50 songs. Supervised approaches should be trained on the training set and tested on both sets.</p>\n\n<p>All files from the <em>musdb18-hq</em> dataset are saved as uncompressed wav files. Within each track folder, the user finds</p>\n\n<ul>\n\t<li>mixture.wav</li>\n\t<li>drums.wav</li>\n\t<li>bass.wav,</li>\n\t<li>other.wav,</li>\n\t<li>vocals.wav</li>\n</ul>\n\n<p>All signals are stereophonic and encoded at 44.1kHz.</p>\n\n<p>&nbsp;</p>\n\n<p>If you use the MUSDB dataset for your research - Cite the MUSDB18 Dataset</p>\n\n<pre><code>@misc{MUSDB18HQ,\n  author       = {Rafii, Zafar and\n                  Liutkus, Antoine and\n                  Fabian-Robert St{\\\"o}ter and\n                  Mimilakis, Stylianos Ioannis and\n                  Bittner, Rachel},\n  title        = {{MUSDB18-HQ} - an uncompressed version of MUSDB18},\n  month        = dec,\n  year         = 2019,\n  doi          = {10.5281/zenodo.3338373},\n  url          = {https://doi.org/10.5281/zenodo.3338373}\n}</code></pre>\n\n<p>If compare your results with SiSEC 2018 Participants - Cite the SiSEC 2018 LVA/ICA Paper</p>\n\n<pre><code>@inproceedings{SiSEC18,\n  author=\"St{\\\"o}ter, Fabian-Robert and Liutkus, Antoine and Ito, Nobutaka\",\n  title=\"The 2018 Signal Separation Evaluation Campaign\",\n  booktitle=\"Latent Variable Analysis and Signal Separation:\n  14th International Conference, LVA/ICA 2018, Surrey, UK\",\n  year=\"2018\",\n  pages=\"293--305\"\n}</code></pre>\n\n<p>&nbsp;</p>", 
  "creator": [
    {
      "affiliation": "Gracenote", 
      "@type": "Person", 
      "name": "Rafii, Zafar"
    }, 
    {
      "affiliation": "INRIA and LIRMM, University of Montpellier", 
      "@type": "Person", 
      "name": "Liutkus, Antoine"
    }, 
    {
      "affiliation": "INRIA and LIRMM, University of Montpellier", 
      "@id": "https://orcid.org/0000-0002-2534-1165", 
      "@type": "Person", 
      "name": "St\u00f6ter, Fabian-Robert"
    }, 
    {
      "affiliation": "Fraunhofer IDMT, Ilmenau", 
      "@type": "Person", 
      "name": "Mimilakis, Stylianos Ioannis"
    }, 
    {
      "affiliation": "Spotify, New York", 
      "@type": "Person", 
      "name": "Bittner, Rachel"
    }
  ], 
  "url": "https://zenodo.org/record/3338373", 
  "datePublished": "2019-08-01", 
  "version": "1.0.0", 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.3338373", 
  "@id": "https://doi.org/10.5281/zenodo.3338373", 
  "@type": "Dataset", 
  "name": "MUSDB18-HQ - an uncompressed version of MUSDB18"
}
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