The electroencephalogram based classification of internally pronounced phonemes
- HCI, UX
The internal speech recognition is a promising technology, which could find its use in brain-computer interfaces development and greatly help those who suffer from neurodegenerative diseases. It is known that internal pronunciation can be restored according to electroencephalogram data because it allows one to register specific activity associated with this process. The purpose of this work is to build and implement an algorithm for extracting features and classifying Russian phonemes according to an electroencephalogram recorded during internal pronunciation of the phonemes.