Abstract
The application of the robot services has been in high demand due to the declining birthrate and aging society. However, one robot’s expression could have different perceptions. Therefore, the purpose of this study is to improve the robot’s impression by estimating human emotions using biological information. Here, a machine learning method was proposed to consider individual differences from the impression evaluation and the combined measurements of electroencephalography (EEG) and pulse rate. This method was evaluated based on three patterns of robot expressions: same as human emotion (synchronize), against human emotion (reverse synchronize), and funny facial expressions. A machine learning method was implied to create a classification model to decide the facial expression of a robot that suits users’ preference. As a result, the individual differences were observed and the machine learning approach reached 80% accuracy.
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References
Nikkei Inc.: Fuji Keizai Group Announces Global Market Research Results for Business and Service Robots. https://www.nikkei.com/article/DGXLRSP534619_W0A520C2000000/. (in Japanese)
Ueda, S., Nojima, K., Murakado, C.: Gender differences in influence of facial expression on facial impression judgments. Jpn. J. Cogn. Psychol. 7(2), 103–112 (2010). (in Japanese)
Ministry of Internal Affairs and Communications: Necessity and issues of partner robots. http://www.soumu.go.jp/johotsusintokei/whitepaper/ja/h27/html/nc241350.html. (in Japanese)
Yamano, M., Hashimoto, M., Usui, T.: Evaluation of human-robot interaction method based on emotional synchronization. In: The Proceedings of JSME Annual Conference on Robotics and Mechatronics (Robomec), 1P1-E08 (2009). (in Japanese)
Kurono, Y., Sripian, P., Chen, F., Sugaya, M.: A preliminary experiment on the emotion of emotion using facial expression and biological signals. In: Human-Computer Interaction. Recognition and Interaction Technologies HCII 2019. LNCS, vol. 11567 (2019)
Sripian, P., Kurono, Y., Yoshida, R., Sugaya, M.: Study of empathy on robot expression based on emotion estimated from facial expression and biological signals. In: 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), pp. 1–8. New Delhi, India (2019)
Kajihara, Y., Sripian, P., Sugaya, M.: Proposal of sympathetic robot by sentiment analysis by biological information and synchronization method of facial expression (biometrics). IEICE Tech. Rep. 119(445), 81–86 (2020). (in Japanese)
Ikeda, Y., Horie, R., Sugaya, M.: Estimate emotion with biological information for robot interaction. In: 21st International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES-2017), pp. 6–8. Marseille, France (2017)
Egawa, S., Sejima, Y., Sato, Y.: Proposal of an estimation method of emotional centroid based on the Russell’s Circumplex model for quantitative evaluation of affect. Trans. Jpn. Soc. Kansei Eng. 18(3), 187–193 (2019). (in Japanese)
Sales Lecture, Human Brain: First impression questionnaire about sales staff. https://itoshin.jp/contents-enquete-report-201307/. (in Japanese)
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Yu, K., Anuardi, M.N.A.M., Sripian, P., Sugaya, M. (2021). An Impression Evaluation of Robot Facial Expressions Considering Individual Differences by Using Biological Information. In: Markopoulos, E., Goonetilleke, R.S., Ho, A.G., Luximon, Y. (eds) Advances in Creativity, Innovation, Entrepreneurship and Communication of Design. AHFE 2021. Lecture Notes in Networks and Systems, vol 276. Springer, Cham. https://doi.org/10.1007/978-3-030-80094-9_61
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DOI: https://doi.org/10.1007/978-3-030-80094-9_61
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