Presentation information

Organized Session

Organized Session » OS-18

[2G5-OS-18a] 脳波から音声言語情報を抽出・識別・利用する(1/2)

Wed. Jun 15, 2022 3:20 PM - 4:40 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)

4:20 PM - 4:40 PM

[2G5-OS-18a-04] Improvement of Syllable Labeling Tool for Electroencephalogram Data

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

Keywords:EEG, Speech Imagery, Annotation Tool

Recently, statistical machine learning and deep learning techniques have been used to make computers learn the correspondence between imagined syllable sequences and feature sequences extracted from electroencephalogram (EEG) signals. These techniques aim to allow a computer to decode linguistic information imagined in a user’s brain. We are developing a labeling tool to efficiently construct training dataset from speech-imagery EEG. In this paper, we propose a labeling support method using the syllable similarity calculated by subspace methods and deep learning.

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