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}