Mapping brain (EEG) signals onto a linguistic space

- reading a Rosetta stone of brain.

Abstract

Recognition of words in speech imagery embedded in electroencephalogram (EEG) signals is one of the challenging technologies for non-invasive brain-computer-interface (BCI). We imitate the reading process of a Rosetta Stone and develop a decoding process of a language system from brain waves (EEG). Eigen-phones, that are extracted from line spectra of EEG signals observed at Broker area, are recognized as the linguistic representation of phones. In this report we present an approach to extract not only segmental information but also suprasegmental information, or accent information.