Food for Thought: How can we exploit contextual embeddings in the translation of idiomatic expressions?

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Abstract

Idiomatic expressions (or idioms) are phrases where the meaning of the phrase cannot be determined from the meaning of the individual words in the expression. Translating idioms between languages is therefore a challenging task. Transformer models based on contextual embeddings have advanced the state-of-the-art across many domains in the field of natural language processing. While research using transformers has advanced both idiom detection as well as idiom disambiguation, idiom translation has not seen a similar advancement. In this work, we investigate two approaches to fine-tuning a pretrained Text-to-Text Transfer Transformer (T5) model to perform idiom translation from English to German. The first approach directly translates English idiom-containing sentences to German, while the second is underpinned by idiom paraphrasing, firstly paraphrasing English idiomatic expressions to their simplified English versions before translating them to German. Results of our evaluation show that each of the approaches is able to generate adequate translations.

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APA

Santing, L., Sijstermans, R., Anerdi, G., Jeuris, P., ten Thij, M., & Batista-Navarro, R. (2022). Food for Thought: How can we exploit contextual embeddings in the translation of idiomatic expressions? In FLP 2022 - 3rd Workshop on Figurative Language Processing, Proceedings of the Workshop (pp. 100–110). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.flp-1.14

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