STATISTICAL LEARNING IN LANGUAGE ACQUISITION

语言习得中的统计学习

• 批准号: 6607704
• 负责人: JENNY R. SAFFRAN
• 金额: $ 9.06万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-08-01 至 2004-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6607704
• 关键词: adult human (21+); behavioral /social science research tag; child psychology; clinical research; human subject; infant human (0-1 year); language development; learning; mathematical model; middle childhood (6-11); psychometrics

The acquisition of language is a daunting task for infants. Research on this process provides an opportunity to address central issues related to the early development of human cognition. This application focuses on statistical language learning mechanisms that detect linguistic units by tracking input patterns of sounds. Recent research suggests that infant learners possess statistical learning mechanisms that may play an important role in language acquisition. Still unknown is the way in which these mechanisms interact to derive linguistic structure, given multiple possibilities. The proposed research addresses these issues by posing the following questions: (1) Can infants perform multiple analyses of the same set of input subsequently, so that the output of one set of statistical computations is the input to the next analysis, and simultaneously, such that multiple levels are processed at once? What factors determine which analysis emerges as the output of the learning process? (2) Do similar constraints on learning, with respect to acoustic and statistical structure, govern statistical language learning by adults, children, and infants? (3) Are the statistical learning mechanisms investigated in (1)-(2) tailored specifically for language learning, or can they operate on stimuli drawn from other domains? These questions will be addressed using previously developed laboratory learning paradigms which permit careful manipulation of the input. The answers to these questions will inform an emerging theoretical framework, constrained statistical learning, intended to elucidate the study of language acquisition and other pressing issues in human learning and development.

对于婴儿来说，语言的习得是一项艰巨的任务。 对这一过程的研究提供了解决核心问题的机会 与人类认知的早期发展有关。此应用程序重点 关于通过以下方式检测语言单位的统计语言学习机制 跟踪声音的输入模式。最近的研究表明，婴儿 学习者拥有的统计学习机制可能发挥重要作用 在语言习得中的作用。仍然未知的是这些 给定多个机制相互作用以得出语言结构 的可能性。拟议的研究通过提出以下问题来解决这些问题 以下问题：（1）婴儿能否对同一组进行多次分析 随后输入，以便输出一组统计数据 计算是下一个分析的输入，同时，这样 一次处理多个级别？哪些因素决定哪些分析 作为学习过程的输出出现？ (2) 做类似的约束 就声学和统计结构而言，学习控制着 成人、儿童和婴儿的统计语言学习？ (3) 是 (1)-(2) 中研究的统计学习机制专门定制 用于语言学习，或者它们可以根据来自其他领域的刺激进行操作吗？ 这些问题将使用先前开发的实验室来解决 允许仔细操作输入的学习范例。答案 这些问题将为新兴的理论框架提供信息， 统计学习，旨在阐明语言习得的研究 以及人类学习和发展中的其他紧迫问题。