Computational and psycholinguistic investigations of covert dependencies

隐性依赖性的计算和心理语言学研究

• 批准号: 1451635
• 负责人: Ming Xiang
• 金额: $ 31.81万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1451635&HistoricalAwards=false
• 关键词: Computational; psycholinguistic; investigations; covert; dependencies

Language is a window into the inner working of the human mind. A great deal of previous work has examined how English speakers understand their mother tongue, and how English speaking children develop their reading, writing and conversational skills to become sufficient English users. Comparatively little is known about whether speakers of different languages adopt qualitatively or quantitatively different strategies in language communication. A good understanding of potential cross-linguistic differences bears directly upon a variety of important issues relevant for U.S. society, including the development of more efficient learning and teaching strategies for foreign languages, and of sophisticated technological tools to extract information from foreign text, websites, and written or spoken corpora. The language under investigation in this project is Mandarin Chinese, which, as the official language of China, is a language with significant national interest to the U.S., due to the growing influence of China's economic and political power. Chinese immigrants also form one of the largest foreign-born groups living in the United States. The particular empirical domain of the current project is on the structure of questions in Chinese. The project consists of two major components. First, a series of behavioral experiments will investigate how Chinese speakers, conditioned by the particular grammatical properties of the Chinese language, make decisions about how to best memorize, recall and anticipate linguistic information encoded in Chinese questions. Second, detailed computational and statistical models will be developed to provide a framework to explain these behaviors. Technological tools will also be developed to work with Chinese corpora. The combination of the behavioral and computational methods makes it possible to answer questions about what differences exist between English and Chinese, and how language users adapt to these differences so as to maximize communicative efficiency in each language. A substantial part of the project also includes training students in cutting-edge research questions, methods, and establishing close international collaboration with leading language researchers and institutions in China.

语言是了解人类思维内部运作的窗口。之前的大量工作都研究了英语使用者如何理解他们的母语，以及英语使用者如何培养他们的阅读、写作和会话技能以成为足够的英语使用者。 关于不同语言的使用者在语言交流中是否采取了质或量上不同的策略，人们知之甚少。 对潜在的跨语言差异的良好理解直接关系到与美国社会相关的各种重要问题，包括开发更有效的外语学习和教学策略，以及从外文文本、网站和书面或口语语料库中提取信息的复杂技术工具。本项目所研究的语言是普通话，作为中国的官方语言，由于中国经济和政治实力的影响力日益增强，对美国而言，普通话是一种具有重大国家利益的语言。 中国移民也是居住在美国的最大的外国出生群体之一。当前项目的具体实证领域是汉语问题的结构。该项目由两个主要部分组成。首先，一系列行为实验将研究汉语使用者如何在汉语特定语法特性的条件下决定如何最好地记忆、回忆和预测汉语问题中编码的语言信息。其次，将开发详细的计算和统计模型，以提供解释这些行为的框架。还将开发与中国语料库配合使用的技术工具。行为和计算方法的结合使得能够回答英语和汉语之间存在哪些差异，以及语言使用者如何适应这些差异以最大化每种语言的交际效率的问题。该项目的很大一部分还包括对学生进行前沿研究问题、方法的培训，以及与中国领先的语言研究人员和机构建立密切的国际合作。