  A social interaction is a social exchange between two or more
individuals,where individuals modify and adjust their behaviors in response to
their interaction partners. Our social interactions are one of most fundamental
aspects of our lives and can profoundly affect our mood, both positively and
negatively. With growing interest in virtual reality and avatar-mediated
interactions,it is desirable to make these interactions natural and human like
to promote positive effect in the interactions and applications such as
intelligent tutoring systems, automated interview systems and e-learning. In
this paper, we propose a method to generate facial behaviors for an agent.
These behaviors include facial expressions and head pose and they are generated
considering the users affective state. Our models learn semantically meaningful
representations of the face and generate appropriate and temporally smooth
facial behaviors in dyadic interactions.
