Let´s talk! Socially intelligent agents for language conversation training

This paper promotes socially intelligent animated agents for the pedagogical task of English conversation training for native speakers of Japanese. As a novel feature, social role awareness is introduced to animated conversational agents, that are by non-strong affective reasoners, but otherwise often lack the social competence observed in humans. In particular, humans may easily adjust their behavior depending on their respective role in a social setting, whereas their synthetic pendants tend to be driven mostly by emotions and personality. Our main contribution is the incorporation of a “social filter program” to mental models of animated agents. This program may qualify an agent´s expression of its emotional state by the social contest, thereby enhancing the agent´s believability as a conversational partner. Our implemented system is web-based and demonstrates socially aware animated agents in a virtual coffee shop environment. An experiment with our conversation system shows that users consider socially aware agents as more natural than agents that violate conventional practices