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HHDS - Spanish HipHop Dataset for Music Source Separation

Martel, Héctor


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    "description": "<p><strong>What is HHDS?</strong></p>\n\n<p>HHDS is a\u00a0reduced compilation of Hip Hop songs,\u00a0used to train a Convolutional Neural Network (CNN) for audio source separation in [1], built on top of the DeepConvSep framework [2] developed at the Music Technology Group (MTG), Universitat Pompeu Fabra.</p>\n\n<p>The structure of HHDS follows the convention of DSD100 [3] (Demixing Secrets Dataset). HHDS contains the separated tracks for the categories of bass, drums, vocals and others in monophonic WAV les with a sampling rate of 44100Hz. The mixture is calculated by normalizing the sum of the tracks. The main difference with respect to DSD100 is that in HHDS there are HipHop songs only, instead of many different genres. The total number of songs is 18, from which 13 are used for training and 5 are used for evaluation.</p>\n\n<p>A detailed\u00a0list of the songs included in the dataset can be found inside the .zip file provided. The reader can also find the code for this dataset in the DeepConvSep repository in the path\u00a0\u00a0examples/hiphopss.</p>\n\n<p>\u00a0</p>\n\n<p><strong>References</strong></p>\n\n<p>[1] \"A Deep Learning Approach to Source Separation and Remixing of\u00a0HipHop music\", H\u00e9ctor Martel, Undergraduate Thesis, Universitat Pompeu Fabra 2016-2017.\u00a0</p>\n\n<p>[2]\u00a0DeepConvSep repository on GitHub: https://github.com/MTG/DeepConvSep</p>\n\n<p>[3]\u00a0Demixing Secrets Dataset (DSD100), SiSEC2016: http://liutkus.net/DSD100.zip</p>", 
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      "source separation, hiphop, audio processing"
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