  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.
