BodyChat: Autonomous communicative behaviors in avatars

Although avatars may resemble animated communicating interface agents, they have for the most part not profited from recent research into autonomous systems. In particular, even though avatars function within conversational environments (for example, chat or games), and even though they often resemble humans (with a head, hands, and a body) they are incapable of representing the kinds of knowledge that humans have about how to use the body during communication. Their appearance does not translate into increased communicative bandwidth. Face-to-face conversation among humans, however, does make extensive use of the visual channel for interaction management where many subtle and even involuntary cues are read from stance, gaze and gesture. We argue that the modeling and animation of such fundamental behavior is crucial for the credibility and effectiveness of the virtual interaction in chat. By treating the avatar as a communicative agent, we propose a method to automate the animation of important communicative behavior, deriving from work in context analysis and discourse theory. BodyChat is a system that allows users to communicate via text while their avatars automatically animate attention, salutations, turn taking, back-channel feedback and facial expression, as well as simple body functions such as the blinking of the eyes.