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        <title>Neural Machine Translation for Coptic-French: Strategies for Low-Resource Ancient Languages</title>
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            <title>Proceedings of the Fourth Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA 2026) @ LREC 2026</title>
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            <namePart type="given">Rachele</namePart>
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    <abstract>This paper presents the first systematic study of strategies for translating Coptic into French. Our comprehensive pipeline systematically evaluates: pivot versus direct translation, the impact of pre-training, the benefits of multi-version fine-tuning, and model robustness to noise. Utilizing aligned biblical corpora, we demonstrate that fine-tuning with a stylistically-varied and noise-aware training corpus significantly enhances translation quality. Our findings provide crucial practical insights for developing translation tools for historical languages in general.</abstract>
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    <identifier type="doi">10.63317/5asa4khfm6hq</identifier>
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%0 Conference Proceedings
%T Neural Machine Translation for Coptic-French: Strategies for Low-Resource Ancient Languages
%A Chaoui, Nasma
%A Khoury, Richard
%Y Sprugnoli, Rachele
%Y Passarotti, Marco
%S Proceedings of the Fourth Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA 2026) @ LREC 2026
%D 2026
%8 May
%I ELRA Language Resources Association (ELRA)
%C Palma, Mallorca (Spain)
%F chaoui-khoury-2026-neural
%X This paper presents the first systematic study of strategies for translating Coptic into French. Our comprehensive pipeline systematically evaluates: pivot versus direct translation, the impact of pre-training, the benefits of multi-version fine-tuning, and model robustness to noise. Utilizing aligned biblical corpora, we demonstrate that fine-tuning with a stylistically-varied and noise-aware training corpus significantly enhances translation quality. Our findings provide crucial practical insights for developing translation tools for historical languages in general.
%R 10.63317/5asa4khfm6hq
%U https://aclanthology.org/2026.lt4hala-1.50/
%U https://doi.org/10.63317/5asa4khfm6hq
%P 482-490

Markdown (Informal)

[Neural Machine Translation for Coptic-French: Strategies for Low-Resource Ancient Languages](https://aclanthology.org/2026.lt4hala-1.50/) (Chaoui & Khoury, LT4HALA 2026)

• Neural Machine Translation for Coptic-French: Strategies for Low-Resource Ancient Languages (Chaoui & Khoury, LT4HALA 2026)

ACL

• Nasma Chaoui and Richard Khoury. 2026. Neural Machine Translation for Coptic-French: Strategies for Low-Resource Ancient Languages. In Proceedings of the Fourth Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA 2026) @ LREC 2026, pages 482–490, Palma, Mallorca (Spain). ELRA Language Resources Association (ELRA).