Efficacy of ByT5 in Multilingual Translation of Biblical Texts for Underrepresented Languages
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arXiv
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| Autori principali: | , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866914816848822272 |
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| author | Aars, Corinne Adams, Lauren Tian, Xiaokan Wang, Zhaoyu Wismer, Colton Wu, Jason Rivas, Pablo Sooksatra, Korn Fendt, Matthew |
| author_facet | Aars, Corinne Adams, Lauren Tian, Xiaokan Wang, Zhaoyu Wismer, Colton Wu, Jason Rivas, Pablo Sooksatra, Korn Fendt, Matthew |
| contents | This study presents the development and evaluation of a ByT5-based multilingual translation model tailored for translating the Bible into underrepresented languages. Utilizing the comprehensive Johns Hopkins University Bible Corpus, we trained the model to capture the intricate nuances of character-based and morphologically rich languages. Our results, measured by the BLEU score and supplemented with sample translations, suggest the model can improve accessibility to sacred texts. It effectively handles the distinctive biblical lexicon and structure, thus bridging the linguistic divide. The study also discusses the model's limitations and suggests pathways for future enhancements, focusing on expanding access to sacred literature across linguistic boundaries. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_13350 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Efficacy of ByT5 in Multilingual Translation of Biblical Texts for Underrepresented Languages Aars, Corinne Adams, Lauren Tian, Xiaokan Wang, Zhaoyu Wismer, Colton Wu, Jason Rivas, Pablo Sooksatra, Korn Fendt, Matthew Computation and Language Machine Learning I.2.7 This study presents the development and evaluation of a ByT5-based multilingual translation model tailored for translating the Bible into underrepresented languages. Utilizing the comprehensive Johns Hopkins University Bible Corpus, we trained the model to capture the intricate nuances of character-based and morphologically rich languages. Our results, measured by the BLEU score and supplemented with sample translations, suggest the model can improve accessibility to sacred texts. It effectively handles the distinctive biblical lexicon and structure, thus bridging the linguistic divide. The study also discusses the model's limitations and suggests pathways for future enhancements, focusing on expanding access to sacred literature across linguistic boundaries. |
| title | Efficacy of ByT5 in Multilingual Translation of Biblical Texts for Underrepresented Languages |
| topic | Computation and Language Machine Learning I.2.7 |
| url | https://arxiv.org/abs/2405.13350 |