Towards Computational Fronesis: Verifying Contextual Appropriateness of Emotions

  • Authors:

  • Michal Ptaszynski;Pawel Dybala;Michal Mazur;Rafal Rzepka;Kenji Araki;Yoshio Momouchi

  • Affiliations:

  • High-Tech Research Center, Hokkai-Gakuen University, Sapporo, Hokkaido, Japan;Department of Information and Management Science, Otaru University of Commerce, Sapporo, Hokkaido, Japan;Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Hokkaido, Japan;Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Hokkaido, Japan;Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Hokkaido, Japan;Department of Electronics and Information Engineering, Faculty of Engineering, Hokkai-Gakuen University, Sapporo, Hokkaido, Japan

  • Venue:
  • International Journal of Distance Education Technologies
  • Year:
  • 2013

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Abstract

This paper presents research in Contextual Affect Analysis CAA for the need of future application in intelligent agents, such as conversational agents or artificial tutors. The authors propose a new term, Computational Fronesis CF, to embrace the tasks included in CAA applied to development of conversational agents such as artificial tutors. In tutor-student discourse it is crucial that the artificial tutor was able not only to detect user/student emotions, but also to verify toward whom they were directed and whether they were appropriate for the context of the conversation. Therefore, as the first task in CF the authors focus on verification of contextual appropriateness of emotions. They performed some of the first experiments in this task for the Japanese language and discuss future directions in development and implications of Computational Fronesis.