A 2-step Framework for Automated Literary Translation Evaluation: Its Promises and Pitfalls

Fuente: arXiv
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Hauptverfasser: Shafayat, Sheikh, Yoon, Dongkeun, Jang, Woori, Choi, Jiwoo, Oh, Alice, Jung, Seohyon
Format: Preprint
Veröffentlicht: 2024
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author Shafayat, Sheikh
Yoon, Dongkeun
Jang, Woori
Choi, Jiwoo
Oh, Alice
Jung, Seohyon
author_facet Shafayat, Sheikh
Yoon, Dongkeun
Jang, Woori
Choi, Jiwoo
Oh, Alice
Jung, Seohyon
contents In this work, we propose and evaluate the feasibility of a two-stage pipeline to evaluate literary machine translation, in a fine-grained manner, from English to Korean. The results show that our framework provides fine-grained, interpretable metrics suited for literary translation and obtains a higher correlation with human judgment than traditional machine translation metrics. Nonetheless, it still fails to match inter-human agreement, especially in metrics like Korean Honorifics. We also observe that LLMs tend to favor translations generated by other LLMs, and we highlight the necessity of developing more sophisticated evaluation methods to ensure accurate and culturally sensitive machine translation of literary works.
format Preprint
id arxiv_https___arxiv_org_abs_2412_01340
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A 2-step Framework for Automated Literary Translation Evaluation: Its Promises and Pitfalls
Shafayat, Sheikh
Yoon, Dongkeun
Jang, Woori
Choi, Jiwoo
Oh, Alice
Jung, Seohyon
Computation and Language
In this work, we propose and evaluate the feasibility of a two-stage pipeline to evaluate literary machine translation, in a fine-grained manner, from English to Korean. The results show that our framework provides fine-grained, interpretable metrics suited for literary translation and obtains a higher correlation with human judgment than traditional machine translation metrics. Nonetheless, it still fails to match inter-human agreement, especially in metrics like Korean Honorifics. We also observe that LLMs tend to favor translations generated by other LLMs, and we highlight the necessity of developing more sophisticated evaluation methods to ensure accurate and culturally sensitive machine translation of literary works.
title A 2-step Framework for Automated Literary Translation Evaluation: Its Promises and Pitfalls
topic Computation and Language
url https://arxiv.org/abs/2412.01340