JSAI2020

Presentation information

Organized Session

Organized Session » OS-15

[4L3-OS-15] OS-15

Fri. Jun 12, 2020 2:00 PM - 3:40 PM Room L (jsai2020online-12)

新田 恒雄(早稲田大学)、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)

2:40 PM - 3:00 PM

[4L3-OS-15-03] Extracting syllables from EEG signal of speech-imagery

〇Kentaro Fukai1, Hidefumi Ohmura1, Kouichi Katsurada1, Satoka Hirata2, Yurie Iribe2, Tsuneo Nitta3,4 (1. Tokyo Univ. of Science, 2. Aichi Prefectural Univ., 3. Waseda Univ., 4. Toyohashi Univ. of Tech.)

Keywords:BCI, EEG signal, speech-imagery, linguistic representation, syllable recognition

Speech imagery recognition from Electroencephalogram (EEG) is one of the challenging technologies for non-invasive brain-computer-interface (BCI). In this report, firstly seventeen syllables appeared in ten Japanese digits are extracted from continuously imagined speech by hand-labelling and evaluated to classify three syllable-groups using Subspace Method (SM). Then, an unlabeled data-set of seventeen short-syllables is collected and tested using 2D-Convolutional NN (CNN). The noise reduction including event related potentials of a prompt pure-tone (ERPs) and the extraction of space-patterns of twenty-one electrodes are also described.

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