BACON: Deep-Learning Powered AI for Poetry Generation with Author Linguistic Style Transfer
This addresses the challenge of creating AI-generated poetry that mimics human authors, though it appears incremental as it combines existing techniques.
The paper tackles the problem of generating poetry with author-specific linguistic style using AI, and the result is that participants could not distinguish between human and AI-generated poems in a statistically significant way.
This paper describes BACON, a basic prototype of an automatic poetry generator with author linguistic style transfer. It combines concepts and techniques from finite state machinery, probabilistic models, artificial neural networks and deep learning, to write original poetry with rich aesthetic-qualities in the style of any given author. Extrinsic evaluation of the output generated by BACON shows that participants were unable to tell the difference between human and AI-generated poems in any statistically significant way.