Verb Learning and The Early Development of Sentence Comprehension: Experimental and Computational Studies

动词学习和句子理解的早期发展：实验和计算研究

• 批准号: 0620257
• 负责人: Cynthia Fisher
• 金额: $ 39.14万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2010-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0620257&HistoricalAwards=false
• 关键词: Verb; Learning; Early; Development; Sentence

With NSF support, Dr. Cynthia Fisher, Dr. Dan Roth, and Dr. Yael Gertner will conduct a three-year study of the early development of sentence comprehension. A fundamental task in sentence comprehension involves assigning semantic roles to sentence constituents, thus determining "who does what to whom". The syntactic bootstrapping theory proposes that even very young children use precursors of the adult's knowledge of syntax to accomplish this task. The project combines experimental and computational approaches to test and refine this theory. The experimental work will investigate 15- to 30-month-olds' sensitivity to proposed simple syntactic cues to sentence interpretation. The computational work involves a system for automatic semantic role labeling; computational models of semantic role labeling learn to identify sentence constituents that fill a semantic role, and to determine their roles, such as agent or goal. The two components of this project will test the proposal that simple aspects of sentence structure guide early sentence comprehension, by examining both successes and tell-tale errors in children's comprehension of sentences, by explicitly modeling learning based on the proposed shallow description of sentence structure, and by comparing the computational model's learning progress and errors to those of the children. This combination of experimental and computational studies is intended both to advance scientific knowledge about how children learn their native languages, and to guide the development of new, robust learning protocols that will be of use in automatic natural language processing.

在NSF的支持下，Cynthia Fisher博士、Dan Roth博士和Yael Gertner博士将对句子理解的早期发展进行为期三年的研究。句子理解的一个基本任务是为句子成分分配语义角色，从而确定“谁对谁做什么”。句法自举理论认为，即使是很小的孩子也会使用成年人的句法知识来完成这项任务。该项目结合了实验和计算方法来测试和完善这一理论。实验工作将调查15至30个月大的婴儿对句子解释的简单句法线索的敏感性。计算工作涉及自动语义角色标注系统;语义角色标注的计算模型学习识别填充语义角色的句子成分，并确定它们的角色，如代理或目标。这个项目的两个组成部分将测试的建议，句子结构的简单方面指导早期句子理解，通过检查成功和告诉故事错误的儿童的句子理解，明确建模学习的基础上提出的句子结构的浅层描述，并通过比较计算模型的学习进度和错误的儿童。这种实验和计算研究的结合旨在推进关于儿童如何学习母语的科学知识，并指导开发新的，强大的学习协议，这些协议将用于自动自然语言处理。