We present a survey covering the state of the art in low-resource machine translation. There are currently around 7000 languages spoken in the world and almost all language pairs lack significant resources for training machine translation models. There has been increasing interest in research addressing the challenge of producing useful translation models when very little translated training data is available. We present a high level summary of this topical field and provide an overview of best practices.
翻译:我们对低资源机器翻译方面的最先进情况进行了调查,目前全世界约有7 000种语言,几乎所有语文对口都缺乏大量资源来培训机器翻译模型,人们越来越有兴趣研究如何在很少有翻译培训数据的情况下,如何应对制作有用的翻译模型的挑战,我们对这一主题领域作了高级别总结,并概述了最佳做法。