CLOct 31, 2023

Erato: Automatizing Poetry Evaluation

arXiv:2310.20326v11 citationsh-index: 10
Originality Synthesis-oriented
AI Analysis

This work addresses the need for automated evaluation tools in poetry generation, but it is incremental as it builds on existing methods without introducing a new paradigm.

The authors tackled the problem of automated poetry evaluation by introducing Erato, a framework that compares human-authored and automatically-generated poetry, demonstrating its effectiveness in identifying key differences.

We present Erato, a framework designed to facilitate the automated evaluation of poetry, including that generated by poetry generation systems. Our framework employs a diverse set of features, and we offer a brief overview of Erato's capabilities and its potential for expansion. Using Erato, we compare and contrast human-authored poetry with automatically-generated poetry, demonstrating its effectiveness in identifying key differences. Our implementation code and software are freely available under the GNU GPLv3 license.

Code Implementations1 repo
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