Bach10 Score-Informed Separation ISMIR2017

<p>This dataset accompanies the paper:<br> M.Miron, J.Janer,E.Gomez,&quot;Monaural score-informed source separation for classical music using convolutional neural networks&quot;, ISMIR 2017,&nbsp;http://mtg.upf.edu/node/3806</p> <p>The files are based on Bach10 dataset which comprises 10 Bach chorales: http://music.cs.northwestern.edu/data/Bach10.html</p> <p>It comprises results in terms of SDR, SIR, SAR as .mat files for the methods presented in the paper.<br> Additionally, we include audio .wav files for the proposed score-informed source separation method using convolutional neural networks and for the score-informed NMF counterpart.</p> <p>The code is available at the github repository: https://github.com/MTG/DeepConvSep/tree/master/examples/bach10_scoreinformed</p> <p>We include the trained CNN model for the proposed approach, which can be used to separate Bach chorales with the code provided at the github repository.&nbsp;</p>