MAD-EEG: an EEG dataset for decoding auditory attention to a target instrument in polyphonic music

The MAD-EEG Dataset is a research corpus for studying EEG-based auditory attention decoding to a target instrument in polyphonic music. 

The dataset consists of 20-channel EEG responses to music recorded from 8 subjects while attending to a particular instrument in a music mixture. 

For further details, please refer to the paper: MAD-EEG: an EEG dataset for decoding auditory attention to a target instrument in polyphonic music.

If you use the data in your research, please reference the paper (not just the Zenodo record):

@inproceedings{Cantisani2019,
author={Giorgia Cantisani and Gabriel Trégoat and Slim Essid and Gaël Richard},
title={{MAD-EEG: an EEG dataset for decoding auditory attention to a target instrument in polyphonic music}},
year=2019,
booktitle={Proc. SMM19, Workshop on Speech, Music and Mind 2019},
pages={51--55},
doi={10.21437/SMM.2019-11},
url={http://dx.doi.org/10.21437/SMM.2019-11}
}