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.
BACON: Deep-Learning Powered AI for Poetry Generation with Author Linguistic Style Transfer
An automatic poetry generator using finite state machinery and deep learning techniques replicates human author styles with high fidelity, achieving indistinguishable results from human-generated poetry.
- Year
- 2021
- Venue
- arXiv 2021
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- 1
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- arxiv.org/abs/2112.11483ARXIV-DEFAULT
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