EEG-Based Silent Speech Interface and its Challenges: A Survey

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.

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