An Analysis of Language Frequency and Error Correction for Esperanto

Junhong Liang
2/15/2024
cs.CL

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Abstract

Current Grammar Error Correction (GEC) initiatives tend to focus on major languages, with less attention given to low-resource languages like Esperanto. In this article, we begin to bridge this gap by first conducting a comprehensive frequency analysis using the Eo-GP dataset, created explicitly for this purpose. We then introduce the Eo-GEC dataset, derived from authentic user cases and annotated with fine-grained linguistic details for error identification. Leveraging GPT-3.5 and GPT-4, our experiments show that GPT-4 outperforms GPT-3.5 in both automated and human evaluations, highlighting its efficacy in addressing Esperanto's grammatical peculiarities and illustrating the potential of advanced language models to enhance GEC strategies for less commonly studied languages.

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Cite this paper

@article{liang2024analysis,
  title  = {An Analysis of Language Frequency and Error Correction for Esperanto},
  author = {Junhong Liang},
  year   = {2024},
  eprint = {2402.09696},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2402.09696v2}
}

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