Romantic-Computing

Elizabeth Horishny

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arXiv · 2206.11864

Romantic-Computing

Elizabeth Horishny

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Abstract

In this paper we compare various text generation models' ability to write poetry in the style of early English Romanticism. These models include: Character-Level Recurrent Neural Networks with Long Short-Term Memory, Hugging Face's GPT-2, OpenAI's GPT-3, and EleutherAI's GPT-NEO. Quality was measured based syllable count and coherence with the automatic evaluation metric GRUEN. Character-Level Recurrent Neural Networks performed far worse compared to transformer models. And, as parameter-size increased, the quality of transformer models' poems improved. These models are typically not compared in a creative context, and we are happy to contribute.

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Elizabeth Horishny. 2022-06-01. Romantic-Computing. https://arxiv.org/abs/2206.11864

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