Dataset Open Access

Bach10 Separation SMC2017

Marius Miron


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        <foaf:name>Marius Miron</foaf:name>
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    <dct:title>Bach10 Separation SMC2017</dct:title>
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    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2017</dct:issued>
    <dcat:keyword>source separation</dcat:keyword>
    <dcat:keyword>classical music</dcat:keyword>
    <dcat:keyword>neural networks</dcat:keyword>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2017-02-28</dct:issued>
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    <dct:description>&lt;p&gt;The Bach10 Separation SMC2017 dataset is derived from the Bach10 dataset, which contains ten pieces of Bach chorales along the scores.&lt;br&gt; We 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:&lt;br&gt; Marius 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&lt;/p&gt; &lt;p&gt;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. &lt;/p&gt; &lt;p&gt;For the intellectual rights and the distribution policy of the original dataset check the Bach10 dataset page:&lt;br&gt; http://music.cs.northwestern.edu/data/Bach10.html&lt;/p&gt; &lt;p&gt;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. &lt;/p&gt; &lt;p&gt;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.&lt;/p&gt;</dct:description>
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