Collaborative Research: RI: Small: NL(V)P:Natural Language (Variety) Processing

没有语言是一块巨石。语言因国家、地区、社会阶层和其他因素而有很大差异。尽管最近自然语言处理（NLP）技术在语言间翻译、回答问题或进行简单对话方面取得了进展，但目前的方法主要集中在语言的“标准”变体上。由于忽略了其他语言，把它们基本上当作统计噪声，当前的技术忽视了说这些语言的数百万人。该项目正在创造方法，使翻译和问答系统等语言技术能够处理和生成细粒度的语言变体。该团队将开发计算方法来自动识别不同语言变体的特征，然后创建将这些语言信息集成到驱动语言技术的模型中的方法。此外，该团队将设计方法，使模型适应各种可能获得最少训练数据的品种。由此产生的一套通用方法将使不同的社区和弱势群体受益，他们说的语言和多样性得不到充分的服务。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

No language is a monolith. Languages vary richly across countries, regions, social classes, and other factors. Despite recent advances in natural language processing (NLP) technology for translating between languages, answering questions, or engaging in simple conversations, current approaches have largely focused only on "standard" varieties of languages. By ignoring other varieties, treating them essentially as statistical noise, current technologies neglect the millions of people who speak these varieties. This project is creating ways to enable language technologies such as translation and question-answering systems, both to process and to generate fine-grained language varieties. The team will develop computational methods to automatically recognize features of different language varieties and then create approaches for integrating such linguistic information into the models powering language technologies. Additionally, the team will design methods to adapt models into varieties for which minimal training data may be available. The resulting suite of general methods will benefit diverse communities and less-privileged populations that speak underserved languages and varieties.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.