EEG-based emotion recognition in Chinese emotional words

Author

Cao, Mengsi ; Fang, Guannan ; Ren, Fuji

Author_Institution

Fac. of Eng., Univ. of Tokushima, Tokushima, Japan

fYear

2011

fDate

15-17 Sept. 2011

Firstpage

452

Lastpage

456

Abstract

Emotion recognition is becoming a more and more hot topic nowadays. Many researches on facial recognition and speech recognition have been done. In this paper, we develop a method to facilitate emotion recognition with electroencephalographic (EEG) signals. The main objective of our study is to reveal the relation between emotional responses and EEG data gathered through giving seven subjects word-imagination stimuli. To induce emotions we choose 20 Chinese emotional words which have relatively high emotional intensities. We use support vector machine (SVM) and linear discriminant analysis (LDA) to recognize emotion, respectively, the average recognition rates of 48.78% and 57.04% could be achieved.

Keywords

electroencephalography; emotion recognition; face recognition; natural language processing; speech recognition; support vector machines; Chinese emotional words; EEG-based emotion recognition; electroencephalographic signals; facial recognition; linear discriminant analysis; speech recognition; support vector machine; word-imagination stimuli; Biomedical monitoring; Electroencephalography; Emotion recognition; Feature extraction; Humans; Physiology; Support vector machines; Chinese emotional words; EEG; SVM; emotion recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud Computing and Intelligence Systems (CCIS), 2011 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-61284-203-5

Type

conf

DOI

10.1109/CCIS.2011.6045108

Filename

6045108