Telem Joyson Singh, Sanabam Boyshana, Sanasam Ranbir Singh, Priyankoo Sarmah · 2026 · arXiv (Cornell University)
DOI: 10.48550/arxiv.2610.29943 · cited by 0 works (OpenAlex) · open-access PDF
印度法院的诉讼是用英语进行的,所以语言与有限翻译技术的使用者有有限的访问权限。我们介绍了印度法院判决的第一个英语Mizo并行数据集。它包含来自高哈提高等法院和印度最高法院的13168个句子对。专业的母语Mizo翻译人员翻译了完整的文档;句子对被手动对齐,两位独立审查员检查了结果。我们的研究发现,英语单词以非常选择性的方式借用:官方和法律术语几乎总是保留在英语中,但日常事物的单词如行动,情况和结果通常以母语Mizo进行翻译。Mizocritics也被用在整个体内不一致。当我们在我们的培训数据上精确调整NLLB 200 1.3B模型时,它在1000对发送的法律
Machine translation (Meta M2M100); the English original follows.
Indian court proceedings are held in English, so speakers of languages with limited translation technology have limited access to them. We present the first English Mizo parallel dataset of Indian court judgments. It contains 13,168 sentence pairs from the Gauhati High Court and the Supreme Court of India. Professional native Mizo translators translated complete documents; sentence pairs were manually aligned, and two independent reviewers checked the results. Our study finds that English words are borrowed in a very selective way: official and legal terms are almost always kept in English, but words for everyday things like actions, situations, and results are usually expressed in native Mizo. Mizo diacritics are also used inconsistently across the corpus. When we fine tune the NLLB 200 1.3B model on our training data, it scores 27.47 BLEU on a balanced legal test set of 1,000 sentence pairs, an improvement of 7.16 BLEU over the base model. However, it still uses English words about three times more often than a human translator does.
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Topics: Sentence, Supreme court, Computer science, Natural language processing, Set (abstract data type), Artificial intelligence
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