Visual Similarity for Socially Interactive Agents that Support Self-Awareness

Self-awareness is a critical factor in social interaction. Teachers being aware of their own emotions and thoughts during class may enable reflection and behavioral change. While inducing self-awareness through mirrors or video is common in face-to-face training, it has been scarcely examined in digital training with virtual avatars. This paper examines the relationship between avatar visual similarity and inducing self-awareness in digital training environments. We developed a theory-based methodology to reliably manipulate perceptually relevant facial features of digital avatars based on human-human identification and emotional predisposition. Manipulating these features allows to create personalized versions of digital avatars with varying degrees of visual similarity.