ChrEn：为濒危语言复兴提供切罗基语-英语机器翻译
ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization
摘要：
切罗基语是切罗基人使用的一种高度濒危的美洲土著语言。切罗基文化深深地嵌入其语言中。然而，世界上大约只有2,000名流利的第一语言切罗基人，而且这个数字每年都在下降。为了拯救这一濒危语言，我们引入了Cherokee-English并行数据集ChrEn，以促进Cherokee和English之间的机器翻译研究。与一些流行的机器翻译语言对相比，ChrEn的资源非常少，总共只包含14 k个句子对。我们以便于域内和域外评估的方式拆分并行数据。我们还收集了5 k Cherokee单语数据，以实现半监督学习。除了这些数据集，我们提出了几个切罗基语-英语和英语-切罗基语机器翻译系统。我们比较了SMT（基于短语）与NMT（基于RNN和基于Transformer）系统;监督与半监督（通过语言模型，反向翻译和BERT/多语言BERT）方法;以及迁移学习与其他4种语言的多语言联合训练。我们最好的结果是15.8/12.7 BLEU的域内和6.5/5.0 BLEU的域外Chr-En/EnChr翻译，分别，我们希望我们的数据集和系统将鼓励社区未来的工作，为切罗基语的复兴。我们的数据、代码和演示将在https://github.com/ZhangShiyue/ChrEn上公开提供
英文摘要：
Cherokee is a highly endangered Native American language spoken by the Cherokee people. The Cherokee culture is deeply embedded in its language. However, there are approximately only 2,000 fluent first language Cherokee speakers remaining in the world, and the number is declining every year. To help save this endangered language, we introduce ChrEn, a Cherokee-English parallel dataset, to facilitate machine translation research between Cherokee and English. Compared to some popular machine translation language pairs, ChrEn is extremely low-resource, only containing 14k sentence pairs in total. We split our parallel data in ways that facilitate both in-domain and out-of-domain evaluation. We also collect 5k Cherokee monolingual data to enable semi-supervised learning. Besides these datasets, we propose several Cherokee-English and English-Cherokee machine translation systems. We compare SMT (phrase-based) versus NMT (RNN-based and Transformer-based) systems; supervised versus semi-supervised (via language model, back-translation, and BERT/Multilingual-BERT) methods; as well as transfer learning versus multilingual joint training with 4 other languages. Our best results are 15.8/12.7 BLEU for in-domain and 6.5/5.0 BLEU for out-of-domain Chr-En/EnChr translations, respectively, and we hope that our dataset and systems will encourage future work by the community for Cherokee language revitalization. Our data, code, and demo will be publicly available at https://github.com/ZhangShiyue/ChrEn
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
