Linguistic Experience and Generalization: Early Links between Sounds,Words, and Grammar

项目总结/摘要 成人的语言知识是围绕着不同层次的语言结构组织起来的：语音类别， 词、子词有意义的单位以及用于将词组合成话语的语法规则。而 人们普遍认为，语言表征的每个层次的学习都依赖于学习， 在其他层次，这些相互作用的确切性质以及学习机制仍然存在 未知这些互动可能会支持“良性循环”，儿童的推理建立在一个 另一个迭代;相互作用也可能引入级联故障的向量， 在一个表征水平上的学习对学习具有广泛的影响。因此，表征 这些学习过程如何相互作用是理解早期语言习得的关键一步， 教育本身是早期识字的决定因素，反过来也是早期教育成就的决定因素。 该项目的重点是英语规则复数的习得， 语言结构，涉及所有这些层次的学习，儿童在早期表现出 灵敏度专注于精心选择的测试案例，可以进行详尽的实验表征， （具体目标1）和模型的发展，捕捉儿童之间的相互作用 不断增长的语音、意义和语法知识（具体目标2）。因此，这项研究 是迈向广泛覆盖的学习与学习之间相互作用的机制模型的第一步， 早期语言习得的过程。早期的语言处理能力是 促进扫盲和教育程度，随后对健康和福祉产生影响。 通过提供一个儿童语言早期习得的增强因果模型，本研究 将帮助研究人员开发更好的诊断方法和设计更好的干预措施。 这里介绍的研究金培训计划的重点是：1）加深申请人对以下方面的了解： 心理语言学建模技术和2）教申请人运行行为实验， 幼儿研究将在两个地点进行：受训人员将从事计算建模工作 在麻省理工学院（主要主办机构，约2/3的奖学金期限），并进行行为 在杜克的实验（约1/3的奖学金时间）。这一多机构设置将 允许学员与具有专业知识，设备和 实现项目目标所需的工具，特别是语言的复杂建模技术。 学习（Levy博士，麻省理工学院）和实验技术评估幼儿的语言知识 (Drs. Bergelson和Tomasello，杜克）。这种导师、实验室和机构的结合， 适合提供必要的培训，以准备申请人终身教授，而 回答关键的突出研究问题。

Project Summary / Abstract Adult language knowledge is organized around different levels of linguistic structure: sound categories, words, sub-word meaningful units, and grammatical rules for combining words into utterances. While it is widely acknowledged that learning at each level of linguistic representation depends on learning at other levels, the precise nature of these interactions, as well as the learning mechanisms, remain unknown. These interactions may support “virtuous cycles” where children's inferences build upon one another iteratively; the interactions may also introduce vectors for cascading failures, where delays in learning at one level of representation have wide-reaching effects on learning. As such, characterizing how these learning processes interact is a critical step towards understanding early language acquisi- tion, itself a determining factor in early literacy, and in turn early educational attainment. The proposed project focuses on the acquisition of the English regular plural, an abstract aspect of language structure which implicates learning at all of these levels, and to which children exhibit an early sensitivity. Focusing on a carefully selected test case allows for exhaustive experimental characteriza- tion (Specific Aim 1) and the development of models that capture the interactions between children's growing knowledge of sounds, meaning, and the grammar (Specific Aim 2). As such, this research constitutes a first step towards a broad-coverage mechanistic model of the interactions between learn- ing processes in early language acquisition. Early language processing abilities are known to be key contributors to literacy and educational attainment, with subsequent effects for health and well-being. By providing an enhanced causal model of children's language early language attainment, this research will help researchers develop better diagnostics and design improved interventions. The fellowship training plan presented here focuses on 1) deepening the applicant's knowledge of psycholinguistic modeling techniques and 2) teaching the applicant to run behavioral experiments with toddlers. The research will be performed at two site: the trainee will work on computational modeling at MIT (primary host institution, approximately 2/3 of the Fellowship duration), and conduct behavioral experiments at Duke (approximately 1/3 of the Fellowship duration). This multi-institution setup will allow the trainee to work with a mentorship team with the specialized knowledge, equipment, and facilities needed to achieve the project goals, especially sophisticated modeling techniques for language learning (Dr. Levy, MIT) and experimental techniques for evaluating the language knowledge of toddlers (Drs. Bergelson and Tomasello, Duke). This combination of mentors, labs, and institutions is perfectly suited to provide the training necessary to prepare the applicant for a tenure-track professorship, while answering critical outstanding research questions.