There Once Was a Really Bad Poet, It Was Automated but You Didn't Know It
Jianyou Wang, Xiaoxuan Zhang, Yuren Zhou, Christopher Suh, Cynthia, Rudin

TL;DR
LimGen is an automated system for limerick generation that combines constraint algorithms, efficient search, and storyline coherence to produce thematically relevant and often humorous poems, outperforming existing models.
Contribution
The paper introduces LimGen, a novel fully automated limerick generation system that integrates multiple algorithms to produce constrained, coherent, and thematically relevant poems.
Findings
LimGen outperforms existing neural and rule-based models.
Generated limericks are both constraint-satisfying and thematically coherent.
Some limericks are notably humorous.
Abstract
Limerick generation exemplifies some of the most difficult challenges faced in poetry generation, as the poems must tell a story in only five lines, with constraints on rhyme, stress, and meter. To address these challenges, we introduce LimGen, a novel and fully automated system for limerick generation that outperforms state-of-the-art neural network-based poetry models, as well as prior rule-based poetry models. LimGen consists of three important pieces: the Adaptive Multi-Templated Constraint algorithm that constrains our search to the space of realistic poems, the Multi-Templated Beam Search algorithm which searches efficiently through the space, and the probabilistic Storyline algorithm that provides coherent storylines related to a user-provided prompt word. The resulting limericks satisfy poetic constraints and have thematically coherent storylines, which are sometimes even funny…
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Taxonomy
TopicsArtificial Intelligence in Games · Topic Modeling · Multimodal Machine Learning Applications
