A User Perception-Based Approach to Create Smiling Embodied Conversational Agents

摘要

In conclusion, the work presented in this article aimed at endowing an ECA with a "smile-focused theory of mind" to automatically infer, during the interaction, the potential user's perception of its social stances depending on its smiling behavior. In order to give the capability to a virtual agent to display different smiling behaviors, we constructed a lexicon of virtual agent smiles including different smile types (amused, embarrassed, and polite). The methodology used to define the morphological and dynamic characteristics of the smiles is based on the design, by the users themselves, of the different types of smile. The proposed algorithm used to extract the smile characteristics from the collected data has the advantage to capture one-to-many correspondence between smile types (amused, embarrassed, and polite) and facial expressions, offering a variability in an ECA's smile expressions. The resulting smiles, evaluated in context through a perceptive study, are fairly consistent with the studies on human smiles, suggesting that users apply common knowledge on human smiles to virtual agents. The different smiles have been integrated in an ECA. Note that, in this article, we have focused on three types of smiles largely studied in interpersonal interaction. In a more exploratory work, we have used unsupervised methods on the user-created smiles to explore new types of smiles without considering a priori typology of smile types [Ochs et al. 2016].