In this paper we highlight the different challenges in modeling communicative gestures for Embodied Conversational Agents (ECAs). We describe models whose aim is to capture and understand the specific characteristics of communicative gestures in order to envision how an automatic communicative gesture production mechanism could be built. The work is inspired by research on how human gesture characteristics (e.g., shape of the hand, movement, orientation and timing with respect to the speech) convey meaning. We present approaches to computing where to place a gesture, which shape the gesture takes and how gesture shapes evolve through time. We focus on a particular model based on theoretical frameworks on metaphors and embodied cognition that argue that people can represent, reason about and convey abstract concepts using physical representations and processes, which can be conveyed through physical gestures.
In the everyday world people form small conversing groups where social interaction takes place, and much of the social behavior takes place through managing interpersonal space (i.e., proxemics) and group formation, signaling their attentio to others (i.e., through gaze behavior), and expressing certain attitudes, for example, friendliness, by smiling, getting close through increased engagement and intimacy, and welcoming newcomers. Many real-time interactive systems feature virtual anthropomorphic characters in order to simulate conversing groups and add plausibility and believability to the simulated environments. However, only a few have dealt with autonomous behavior generation, and in those cases, the agents’ exhibited behavior should be evaluated by users in terms of appropriateness, believability, and conveyed meaning (e.g., attitudes). In this article we present an integrated intelligent interactive system for generating believable nonverbal behavior exhibited by virtual agents in small simulated group conversations. The produced behavior supports group formation management and the expression of interpersonal attitudes (friendly vs. unfriendly) both among the agents in the group (i.e., in-group attitude) and towards an approaching user in an avatar-based interaction (out-group attitude). A user study investigating the effects of these attitudes on users’ social presence evaluation and proxemics behavior (with their avatar) in a three-dimensional virtual city environment is presented. We divided the study into two trials according to the task assigned to users, that is, joining a conversing group and reaching a target destination behind the group. Results showed that the out-group attitude had a major impact on social presence evaluations in both trials, whereby friendly groups were perceived as more socially rich. The user’s proxemics behavior depended on both out-group and in-group attitudes expressed by the agents. Implications of these results for the design and implementation of similar intelligent interactive systems for the autonomous generation of agents’ multimodal behavior are briefly discussed.
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