Dataset Open Access
Marius Miron
{ "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": "https://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", "encodingFormat": "gz", "@type": "DataDownload" } ], "identifier": "https://doi.org/10.5281/zenodo.344499", "@id": "https://doi.org/10.5281/zenodo.344499", "@type": "Dataset", "name": "Bach10 Separation SMC2017" }
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Data volume | 43.4 GB | 43.4 GB |
Unique views | 214 | 215 |
Unique downloads | 34 | 34 |