Large Language Models for Persian $ \leftrightarrow $ English Idiom Translation

• URL: http://arxiv.org/abs/2412.09993v2
• Date: Fri, 21 Feb 2025 21:45:48 GMT
• Title: Large Language Models for Persian $ \leftrightarrow $ English Idiom Translation
• Authors: Sara Rezaeimanesh, Faezeh Hosseini, Yadollah Yaghoobzadeh,
• Abstract summary: Large language models (LLMs) have shown superior capabilities in translating figurative language compared to neural machine translation (NMT) systems.<n>This paper introduces two parallel datasets of sentences containing idiomatic expressions for Persian$rightarrow$English and English$rightarrow$Persian translations.<n>We evaluate various open- and closed-source LLMs, NMT models, and their combinations.<n>Experiments reveal that Claude-3.5-Sonnet delivers outstanding results in both translation directions.
• Score: 5.689194193929357
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large language models (LLMs) have shown superior capabilities in translating figurative language compared to neural machine translation (NMT) systems. However, the impact of different prompting methods and LLM-NMT combinations on idiom translation has yet to be thoroughly investigated. This paper introduces two parallel datasets of sentences containing idiomatic expressions for Persian$\rightarrow$English and English$\rightarrow$Persian translations, with Persian idioms sampled from our PersianIdioms resource, a collection of 2,200 idioms and their meanings, with 700 including usage examples. Using these datasets, we evaluate various open- and closed-source LLMs, NMT models, and their combinations. Translation quality is assessed through idiom translation accuracy and fluency. We also find that automatic evaluation methods like LLM-as-a-judge, BLEU, and BERTScore are effective for comparing different aspects of model performance. Our experiments reveal that Claude-3.5-Sonnet delivers outstanding results in both translation directions. For English$\rightarrow$Persian, combining weaker LLMs with Google Translate improves results, while Persian$\rightarrow$English translations benefit from single prompts for simpler models and complex prompts for advanced ones.

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