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)

3:20 PM - 3:40 PM

[4L3-OS-15-05] Semi-automatic Syllable Alignment to Improve Efficiency of Labelling to Speech-imagery EEG Data

〇Ryo Taguchi1, Mingchua Fu 1, Tsuneo Nitta2,3 (1. Nagoya Institute of Technology, 2. Waseda University, 3. Toyohashi University of Technology)

Keywords:Electroencephalogram, Syllable Labelling, HMM

EEG (Electroencephalogram) is an electrical signal representing activity of the brain and have been used for healthcare and brain-machine interface. Recently, researches to estimate imagined linguistic information from EEG signals were launched. These researches need to make labeled EEG dataset that are given boundaries of imagined syllables. In this paper, we propose a semi-automatic syllable alignment method to improve efficiency of the manual labeling to EEG data.

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