Towards Computational Fronesis

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.

ML-Ask: Open Source Affect Analysis Software for Textual Input in Japanese

“…This was evaluated using only ML-Ask [3,4], and ML-Ask confronted with the Webmining procedure [23,26]. Recently Ptaszynski et al added also emoticon analysis system CAO to this evaluation [35].…”