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- W4313131467 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." @default.
- W4313131467 created "2023-01-06" @default.
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- W4313131467 date "2022-01-01" @default.
- W4313131467 modified "2023-10-14" @default.
- W4313131467 title "EEG-Based Silent Speech Interface and its Challenges: A Survey" @default.
- W4313131467 doi "https://doi.org/10.14569/ijacsa.2022.0131173" @default.
- W4313131467 hasPublicationYear "2022" @default.
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