Formal Models of Human Sentence Processing: Techniques and Tools

人类句子处理的形式模型：技术和工具

• 批准号: 0725003
• 负责人: Peter Gordon
• 金额: $ 1.82万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-11-01 至 2008-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0725003&HistoricalAwards=false
• 关键词: Formal; Models; Human; Sentence; Processing

In what ways are human language and formal, computer-based languages similar? In what ways are they different? How can understanding of human languages lead to more effective computer languages and how can the explicit formalization offered by computer languages be used to increase understanding of how humans use language? These questions are central to efforts to understand language as a cognitive activity, an activity that plays a critical role in communicating, transforming, storing and retrieving information. With NSF funding, language researchers at the University of North Carolina at Chapel Hill will bring together the world's leading researchers to address these basic questions in a special sentence of the 21st Annual CUNY Conference on Human Sentence Processing in Chapel Hill, North Carolina in March 2008. In this special session, the latest developments in formal models of language processing, using techniques developed in computer science, neural network research and statistics will be applied to human language use. In addition, the special session will address how the sharing of formal tools (e.g., model simulations, datasets, and statistical procedures) could have a transformative effect on the study of human sentence processing by facilitating wider use of formal methods and by providing a way in which this research community could more effectively exploit advances in modeling and statistical analysis that have been developed in other scientific domains.The Annual CUNY Conference on Human Sentence Processing is the most prominent meeting of high-level language-processing researchers in the world. In addition to directly supporting the special session on formal models, NSF funding will help support the participation of beginning investigators, including starting faculty, post-doctoral researchers and graduate students, and so will facilitate entry of new generations of researchers into the language sciences.

人类语言和基于计算机的正式语言在哪些方面相似？ 它们在哪些方面有所不同？ 对人类语言的理解如何导致更有效的计算机语言以及如何使用计算机语言提供的显式形式化来增进对人类如何使用语言的理解？ 这些问题对于将语言理解为一种认知活动至关重要，这种活动在交流、转换、存储和检索信息中发挥着关键作用。 在 NSF 的资助下，北卡罗来纳大学教堂山分校的语言研究人员将在 2008 年 3 月于北卡罗来纳州教堂山举行的第 21 届纽约市立大学人类句子处理年会上的一个特别句子中，汇集世界领先的研究人员来解决这些基本问题。在这次特别会议中，语言处理形式模型的最新发展，将使用计算机科学、神经网络研究和统计学中开发的技术，应用于人类语言的使用。 此外，特别会议将讨论形式化工具（例如模型模拟、数据集和统计程序）的共享如何通过促进形式化方法的更广泛使用以及通过提供一种方式使研究界能够更有效地利用其他科学领域已开发的建模和统计分析的进展，从而对人类句子处理的研究产生变革性的影响。纽约市立大学年度人类句子处理会议是人类句子处理最重要的会议。 世界上高级语言处理研究人员。 除了直接支持形式模型特别会议外，国家科学基金会的资助还将帮助支持新研究人员的参与，包括新教师、博士后研究人员和研究生，从而促进新一代研究人员进入语言科学领域。