EEG Database for language detection.
Loading...
Identifiers
Publication date
Reading date
Collaborators
Advisors
Tutors
Editors
Journal Title
Journal ISSN
Volume Title
Publisher
Universidad de Málaga
Share
Department/Institute
Referenced by
Isaac Ariza, Ana M. Barbancho, Lorenzo J. Tardón, Isabel Barbancho, Energy-based features and bi-LSTM neural network for EEG-based music and voice classification. Neural Comput & Applic 36, 791–802 (2024). https://doi.org/10.1007/s00521-023-09061-3
Abstract
This database is made up of EEG signals from 6 subjects listening to sentences in different languages and their answers to the questions: have you understood the meaning of the sentence?. The languages chosen are: english, german, italian, korean and spanish.
These signals have been captured with the BrainVision actiCHAMP-PLUS system and consist of a total of 64 EEG channels. The BrainVision Recorder software was used to store the signals. The stimulus presentation software used to design the experiment is Eprime 3.
For more detailed information on this database, the capture system used and its applications, see [1].
If these data are used for any publication, the following paper must be cited:
[1] Isaac Ariza, Ana M. Barbancho, Lorenzo J. Tardón, Isabel Barbancho, Energy-based features and bi-LSTM neural network for EEG-based music and voice classification. Neural Comput & Applic 36, 791–802 (2024). https://doi.org/10.1007/s00521-023-09061-3
Description
Bibliographic citation
Collections
Endorsement
Review
Supplemented By
Referenced by
Creative Commons license
Except where otherwised noted, this item's license is described as Attribution-NonCommercial 4.0 Internacional











