Dataset Open Access

Bach10 Score-Informed Separation ISMIR2017

Marius Miron

This dataset accompanies the paper:
M.Miron, J.Janer,E.Gomez,"Monaural score-informed source separation for classical music using convolutional neural networks", ISMIR 2017, http://mtg.upf.edu/node/3806

The files are based on Bach10 dataset which comprises 10 Bach chorales: http://music.cs.northwestern.edu/data/Bach10.html

It comprises results in terms of SDR, SIR, SAR as .mat files for the methods presented in the paper.
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.

The code is available at the github repository: https://github.com/MTG/DeepConvSep/tree/master/examples/bach10_scoreinformed

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. 

Files (148.7 MB)
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Bach10scoreinformed.zip
md5:bef4aa4eece580d70d415e4e182bf0b5
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