论文标题
低资源语言：对过去的工作和未来挑战的评论
Low-resource Languages: A Review of Past Work and Future Challenges
论文作者
论文摘要
NLP中的当前问题是按摩和处理低资源语言，这些语言缺乏有用的培训属性，例如监督数据，母语人士或专家的数量等。本综述论文简单地总结了以前的开创性成就，用于解决此问题，并分析了整个未来研究方向的潜在改进。
A current problem in NLP is massaging and processing low-resource languages which lack useful training attributes such as supervised data, number of native speakers or experts, etc. This review paper concisely summarizes previous groundbreaking achievements made towards resolving this problem, and analyzes potential improvements in the context of the overall future research direction.
