There is a newer version of the record available.

Published August 30, 2019 | Version 1.0.0
Dataset Restricted

Auditory Attention Detection Dataset KULeuven (OLD VERSION)

Creators

  • 1. KU Leuven

Contributors

Data collector:

  • 1. KU Leuven

Description

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Disclaimer: PLEASE DO NOT USE THIS VERSION (Data has been made unavailable)

Another version, version 1.1.0, of this data set is available here, which contains the original data (+ details on the data set). The version published on the current page contains EEG data that has been pre-processed with a data-driven artifact removal procedure on a trial-by-trial basis. This can introduce slight differences across trials that can possibly be exploited by classifiers. Therefore, for proper benchmarking of auditory attention decoding algorithms that can learn to use such cues, it is recommended to NOT use this pre-processed data set, and instead use the unprocessed version 1.1.0 (the original data).

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This  version of the data set was used in

Das, N., Vanthornhout, J., Francart, T., & Bertrand, A.  “Stimulus-aware spatial filtering for single-trial neural response and temporal response function estimation in high-density EEG with applications in auditory research.” NeuroImage, Volume 204, 116211, Jan. 2020
https://doi.org/10.1016/j.neuroimage.2019.116211

The results and conclusions in the paper are not affected by the trial-by-trial application of the artifact removal procedure.

Notes

This research work was carried out at the ESAT and ExpORL Laboratories of KU Leuven, in the frame of KU Leuven Special Research Fund BOF/ STG-14-005, OT/14/119 and C14/16/057. The work has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No 637424).

Files

Restricted

The record is publicly accessible, but files are restricted to users with access.

Additional details

References

  • Biesmans, W., Das, N., Francart, T., & Bertrand, A. (2016). Auditory-inspired speech envelope extraction methods for improved EEG-based auditory attention detection in a cocktail party scenario. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(5), 402-412.