  There is a growing recognition that artists use valuable ways to understand
and work with cognitive and perceptual mechanisms to convey desired experiences
and narrative in their created artworks (DiPaola et al., 2010; Zeki, 2001).
This paper documents our attempt to computationally model the creative process
of a portrait painter, who relies on understanding human traits (i.e.,
personality and emotions) to inform their art. Our system includes an empathic
conversational interaction component to capture the dominant personality
category of the user and a generative AI Portraiture system that uses this
categorization to create a personalized stylization of the user's portrait.
This paper includes the description of our systems and the real-time
interaction results obtained during the demonstration session of the NeurIPS
2019 Conference.
