An Analysis of Language Frequency and Error Correction for Esperanto
<|reference_start|>An Analysis of Language Frequency and Error Correction for Esperanto: 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.<|reference_end|>
@article{liang2024an,
    title={An Analysis of Language Frequency and Error Correction for Esperanto},
    author={Junhong Liang},
    journal={arXiv preprint arXiv:2402.09696},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.09696},
    primaryClass={cs.CL}
}