Abstract: People with speech disorders could have social and welfare difficulties. Therefore, the silent speech interface (SSI) is needed to help them communicate. This interface decodes the speech from a human’s biosignal. The brain signals contain information from speech production to cover people with numerous speech disorders. Brain signals can be acquired non-invasively by electroencephalograph (EEG) and later transformed into the features for the input of speech pattern recognition. This review discusses the advancement of EEG-based SSI research and its current challenges. It mainly discussed the acquisition protocol, spectral-spatial-temporal characterization of EEG-based imagined speech, classification techniques with leave-one-subject or session-out cross-validation, and related real-world environmental issues. It aims to aid future imagined speech decoding research in exploring the proper methods to overcome the problems.

Nilam Fitriah, Hasballah Zakaria and Tati Latifah Erawati Rajab, “EEG-Based Silent Speech Interface and its Challenges: A Survey” International Journal of Advanced Computer Science and Applications(IJACSA), 13(11), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0131173

@article{Fitriah2022,
title = {EEG-Based Silent Speech Interface and its Challenges: A Survey},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131173},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131173},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {11},
author = {Nilam Fitriah and Hasballah Zakaria and Tati Latifah Erawati Rajab}
}