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Empathic AI Painter: A Computational Creativity System with Embodied Conversational Interaction


There is a growing recognition that artists use valuable ways to understand and workwith cognitive and perceptual mechanisms to convey desired experiences and narrativein their created artworks (DiPaola et al., 2010; Zeki, 2001). This paper documents ourattempt to computationally model the creative process of a portrait painter, who relieson understanding human traits (i.e., personality and emotions) to inform their art. Oursystem includes an empathic conversational interaction component to capture the dominantpersonality category of the user and a generative AI Portraiture system that uses thiscategorization to create a personalized stylization of the user’s portrait. This paper includesthe description of our systems and the real-time interaction results obtained during thedemonstration session of the NeurIPS 2019 Conference.

In Proceedings of Machine Learning Research (NeurIPS 2019 Competition and Demonstration Track).