Efficacy of ByT5 in Multilingual Translation of Biblical Texts for Underrepresented Languages
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Abstract (arXiv)
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.
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References · 6
- 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
- 2018Deep contextualized word representationscited by 2,290
- 2022No Language Left Behind: Scaling Human-Centered Machine Translationcited by 1,312
- 2019Neural Machine Translation with Byte-Level Subwordscited by 115
- 2021How to Adapt Your Pretrained Multilingual Model to 1600 Languagescited by 54
- 2023How do different tokenizers perform on downstream tasks in scriptio continua languages?: A case study in Japanesecited by 20
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