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

Özge Nilay Yalçın, Nouf Abukhodair, Steve DiPaola
Proceedings of the NeurIPS 2019 Competition and Demonstration Track, PMLR 123:131-141, 2020.

Abstract

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. 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.

Cite this Paper

BibTeX
@InProceedings{pmlr-v123-yalcin20a, title = {Empathic AI Painter: A Computational Creativity System with Embodied Conversational Interaction}, author = {Yal\c{c}{\i}n, \"Ozge Nilay and Abukhodair, Nouf and DiPaola, Steve}, booktitle = {Proceedings of the NeurIPS 2019 Competition and Demonstration Track}, pages = {131--141}, year = {2020}, editor = {Escalante, Hugo Jair and Hadsell, Raia}, volume = {123}, series = {Proceedings of Machine Learning Research}, month = {08--14 Dec}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v123/yalcin20a/yalcin20a.pdf}, url = {https://proceedings.mlr.press/v123/yalcin20a.html}, abstract = {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. 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.} }
Endnote
%0 Conference Paper %T Empathic AI Painter: A Computational Creativity System with Embodied Conversational Interaction %A Özge Nilay Yalçın %A Nouf Abukhodair %A Steve DiPaola %B Proceedings of the NeurIPS 2019 Competition and Demonstration Track %C Proceedings of Machine Learning Research %D 2020 %E Hugo Jair Escalante %E Raia Hadsell %F pmlr-v123-yalcin20a %I PMLR %P 131--141 %U https://proceedings.mlr.press/v123/yalcin20a.html %V 123 %X 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. 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.
APA
Yalçın, Ö.N., Abukhodair, N. & DiPaola, S.. (2020). Empathic AI Painter: A Computational Creativity System with Embodied Conversational Interaction. Proceedings of the NeurIPS 2019 Competition and Demonstration Track, in Proceedings of Machine Learning Research 123:131-141 Available from https://proceedings.mlr.press/v123/yalcin20a.html.

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