ArEEG_Chars: Dataset for Envisioned Speech Recognition using EEG for Arabic Characters
<|reference_start|>ArEEG_Chars: Dataset for Envisioned Speech Recognition using EEG for Arabic Characters: Brain-Computer-Interface (BCI) has been a hot research topic in the last few years that could help paralyzed people in their lives. Several researches were done to classify electroencephalography (EEG) signals automatically into English characters and words. Arabic language is one of the most used languages around the world. However, to the best of our knowledge, there is no dataset for Arabic characters EEG signals. In this paper, we have created an EEG dataset for Arabic characters and named it ArEEG_Chars. Moreover, several experiments were done on ArEEG_Chars using deep learning. Best results were achieved using LSTM and reached an accuracy of 97%. ArEEG_Chars dataset will be public for researchers.<|reference_end|>
@article{darwish2024areeg_chars:,
    title={ArEEG_Chars: Dataset for Envisioned Speech Recognition using EEG for
  Arabic Characters},
    author={Hazem Darwish and Abdalrahman Al Malah and Khloud Al Jallad and Nada
  Ghneim},
    journal={arXiv preprint arXiv:2402.15733},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.15733},
    primaryClass={cs.HC cs.CL cs.LG eess.SP}
}