Electroencephalogram (EEG) Imagined Speech Recognition using Deep Learning Approach of Convolutional Neural Network

カテゴリ: 研究会(論文単位)

論文No: CMN21027

グループ名: 【C】電子・情報・システム部門 通信研究会

発行日: 2021/03/23

タイトル(英語): Electroencephalogram (EEG) Imagined Speech Recognition using Deep Learning Approach of Convolutional Neural Network

著者名: YIAM KAR KAR(UNIVERSITI PUTRA MALAYSIA),AL-HADDAD SYED ADBUL RAHMAN(UNIVERSITI PUTRA MALAYSIA),ARIS ISHAK(UNIVERSITI PUTRA MALAYSIA)

著者名(英語): KAR KAR YIAM(UNIVERSITI PUTRA MALAYSIA),SYED ADBUL RAHMAN AL-HADDAD(UNIVERSITI PUTRA MALAYSIA),ISHAK ARIS(UNIVERSITI PUTRA MALAYSIA)

キーワード: EEG|CNN|Neuro Recognition|Classification|Imagined Speech|Deep Learning|EEG|CNN|Neuro Recognition|Classification|Imagined Speech|Deep Learning

要約(日本語): Imagined Speech is gaining an attraction as a communication paradigm in communication aids applications that are potentially widely used in disable people that had difficulties in verbalising their thoughts. The evolution of research development indicates the potential of decoding the imagined speech directly from the human brain via the use of acquired Electroencephalogram (EEG) signals. The goal of this research project is to develop a classifier using a deep learning approach of Convolutional Neural Network that is used to perform the classification of EEG Imagined Speech correctly and convert it into a readable text.

要約(英語): Imagined Speech is gaining an attraction as a communication paradigm in communication aids applications that are potentially widely used in disable people that had difficulties in verbalising their thoughts. The evolution of research development indicates the potential of decoding the imagined speech directly from the human brain via the use of acquired Electroencephalogram (EEG) signals. The goal of this research project is to develop a classifier using a deep learning approach of Convolutional Neural Network that is used to perform the classification of EEG Imagined Speech correctly and convert it into a readable text.

本誌: 2021年3月26日－2021年3月27日通信研究会

本誌掲載ページ: 51-54 p

原稿種別: 英語

PDFファイルサイズ: 1,095 Kバイト