This study presents the development and evaluation of a ByteT5-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.

本研究提出了一种基于 ByteT5 的多语言翻译模型，旨在将圣经翻译成少数语言。通过使用约翰・霍普金斯大学圣经语料库进行训练，我们使模型能够捕捉基于字符和形态丰富的语言的复杂细微差别。我们的结果通过 BLEU 分数和样本翻译进行衡量，表明该模型可以提高对神圣文本的可访问性。它有效地处理了独特的圣经词汇和结构，从而弥合了语言分歧。本研究还讨论了模型的局限性，并提出了未来增强的途径，重点是在跨语言界限上扩大对神圣文学的获取。