EEG-Based Discrimination of Imagined Speech Phonemes

This paper reports positive results for classifying imagined phonemes on the basis of EEG signals. Subjects generated in imagination five types of phonemes that differ in their primary manner of vocal articulation during overt speech production (jaw, tongue, nasal, lips and fricative). Naive Bayes and linear discriminant analysis classification methods were applied to EEG signals that were recorded during imagined phoneme production. Results show that signals from these classes can be differentiated from those generated during periods of no imagined speech and that the signals among the classes are discriminable, particularly in data collected on a single day. The simple linear classification methods are suited well to online use in BCI applications.