Presentation information

Organized Session

Organized Session » OS-18

[2G6-OS-18b] 脳波から音声言語情報を抽出・識別・利用する(2/2)

Wed. Jun 15, 2022 5:20 PM - 6:20 PM Room G (Room G)

オーガナイザ:新田 恒雄(豊橋技術科学大学)[現地]、桂田 浩一(東京理科大学)、入部 百合絵(愛知県立大学)、田口 亮(名古屋工業大学)、篠原 修二(東京大学)

5:20 PM - 5:40 PM

[2G6-OS-18b-01] Phoneme recognition from speech-imagery EEG

〇Motoharu Yamao1, Yurie Iribe1, Ryo Taguchi2, Kouichi Katsurada3, Tsuneo Nitta4 (1. Aichi Prefectural University, 2. Nagoya Institute of Technology, 3. Tokyo University of Science, 4. Toyohashi University of Technology)

Keywords:BCI, EEG, speech-imagery, language symbol, phoneme recognition

Speech imagery recognition from Electroencephalogram (EEG) is one of challenging technologies for non-invasive brain-computer-interface (BCI). In this report, we propose a new method to identify vowels with three features extracted from EEG signals of continuously imagined speech. The features mean line spectra detected spectral peaks using linear predictive analysis (LPA), its frequency direction derivative, and bilinear calculated tensor product of compressed line spectra. In experiments, the recognition rate was obtained approximately 73.1% by using Convolutional Neural Network (CNN). It is clear that these features are effective for vowel recognition from EEG signals of continuously imagined speech.

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