首个支持三种语言互译的神经机器翻译系统，助力濒危语言保护。
Neural machine translation system for Lezgian, Russian and Azerbaijani languages
- 构建多语言神经翻译模型，支持俄语、阿塞拜疆语与莱兹金语互译。
- 在莱兹金-阿塞拜疆语对上达到26.14的BLEU得分，表现良好。
- 开源数据集与模型，适合濒危语言研究与低资源翻译方向。
我们发布了首个用于俄语、阿塞拜疆语和濒危语言莱兹金语之间互译的神经机器翻译系统，并提供了用于训练与评估的平行语料库与单语语料库。通过多项实验，研究了不同训练语料对翻译质量的影响。在莱兹金-阿塞拜疆语对上取得26.14的BLEU得分，阿塞拜疆语-莱兹金语为22.89，莱兹金语-俄语为29.48，俄语-莱兹金语为24.25。在大语言模型上评估零样本翻译，结果显示莱兹金语表达流畅度高，但模型常以自身能力不足为由拒绝翻译。我们公开了翻译模型、平行与单语语料库及莱兹金语句向量编码器。
原文摘要 · Abstract (English)
We release the first neural machine translation system for translation between Russian, Azerbaijani and the endangered Lezgian languages, as well as monolingual and parallel datasets collected and aligned for training and evaluating the system. Multiple experiments are conducted to identify how different sets of training language pairs and data domains can influence the resulting translation quality. We achieve BLEU scores of 26.14 for Lezgian-Azerbaijani, 22.89 for Azerbaijani-Lezgian, 29.48 for Lezgian-Russian and 24.25 for Russian-Lezgian pairs. The quality of zero-shot translation is assessed on a Large Language Model, showing its high level of fluency in Lezgian. However, the model often refuses to translate, justifying itself with its incompetence. We contribute our translation model along with the collected parallel and monolingual corpora and sentence encoder for the Lezgian language.
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