Empathic AI Painter: A Computational Creativity System with Embodied Conversational Interaction
This work addresses the challenge of creating personalized AI-generated art for users, though it appears incremental as it builds on existing computational creativity and generative AI methods.
The paper tackles the problem of computationally modeling a portrait painter's creative process by developing a system that uses empathic conversational interaction to capture a user's personality and then generates a personalized stylized portrait based on that categorization, with results demonstrated in real-time at the NeurIPS 2019 Conference.
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.