Authors:
Kei Hasegawa
;
Hikaru Miyamoto
;
Yuki Ashida
;
Yuki Ban
;
Rui Fukui
;
Masahiro Inazawa
and
Shin’ichi Warisawa
Affiliation:
Development of Human and Engineered Environmental Studies, The Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba, Japan
Keyword(s):
Affective Computing, Computer-Mediated Communication, Keyboard, Support Vector Machine.
Abstract:
In recent years, the use of computer-mediated communication (CMC), that is, communication among people through computers, has increased. Knowing the message sender’s affective state is essential for understanding the contents of the message correctly. However, it is difficult to interpret this state because of the nonavailability of nonverbal information from the sender during CMC. Although attempts have been performed to estimate affective state, there is a challenge of high measurement load. In this paper, we propose an estimation of valence and arousal using keyboard input and typing vibration information as a method to estimate the sender’s affective state with a low measurement load during CMC. We conducted experiments to obtain keyboard input and typing vibration information for estimating valence and arousal. This estimation was performed by extracting features from the information using a support vector machine, and cross-validation was conducted to verify our method. Therefo
re, the valence and arousal were estimated at accuracies of 69.8% and 71.1%, respectively, for unlearned participants’ data.
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