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

语言经验和概括：声音、单词和语法之间的早期联系

• 批准号: 10054653
• 负责人: Stephan Charles Meylan
• 金额: $ 6.64万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-11-01 至 2022-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10054653
• 关键词: Adult; Age; Agreement; Bayesian Modeling; Behavioral; Canis familiaris; Categories; Child; Child Language; Cognitive Science; Complex; Comprehension; Computer Models; Data Set; Development; Diagnostic; Educational process of instructing; Equipment; Evaluation; Exhibits; Failure; Felis catus; Fellowship; Goals; Health; Home; Institution; Intervention; Knowledge; Language; Language Delays; Language Development; Learning; Linguistics; Link; Mentors; Mentorship; Modeling; Morphology; Nature; Nursery Schools; Personal Satisfaction; Phonetics; Process; Production; Psycholinguistics; Research; Research Personnel; Risk; Running; Salvelinus; Seedling; Site; Speech; Structure; System; Techniques; Testing; Toddler; Training; Voice; Work; causal model; design; developmental psychology; early childhood; effective intervention; exhaustion; experience; experimental study; hands-on learning; improved; infancy; interest; laboratory experiment; language processing; literacy; model development; multilevel analysis; novel; pedagogy; sound; syntax; tenure track; theories; vector

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.

项目摘要/摘要 成人语言知识围绕不同层次的语言结构进行组织：声音类别， 单词、子词有意义的单位和将单词组合成话语的语法规则。而当 人们普遍认为，在语言表达的每一个层面上的学习都取决于学习 在其他层面上，这些互动的确切性质以及学习机制仍然存在 未知。这些相互作用可能会支持儿童的推理建立在一个基础上的“良性循环” 另一种迭代方式；交互还可能引入级联故障的向量，其中延迟 在一个表征水平上的学习对学习有广泛的影响。因此，将其描述为 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性因素，进而影响早期教育成就。 拟议的项目侧重于英语规则复数的习得，这是英语的一个抽象方面 一种语言结构，涉及所有这些水平的学习，儿童表现出早期的 敏感度。专注于精心选择的测试用例可以进行详尽的实验特征- Ttion(Speciific Aim 1)和开发捕捉儿童之间相互作用的模型 不断增长的声音、意义和语法知识(特殊fic目标2)。因此，这项研究 构成了fi朝着广泛覆盖的学习和学习之间相互作用的机制模型迈出的第一步 ING在早期语言习得过程中的作用。众所周知，早期的语言处理能力是关键 对识字和教育成就的贡献者，以及随后对健康和福祉的影响。 通过提供一个增强的儿童语言早期语言习得的因果模型，本研究 将帮助研究人员开发更好的诊断方法并设计改进的干预措施。 这里提出的奖学金培训计划侧重于1)加深申请者对以下方面的了解 心理语言学建模技术和2)教申请者进行行为实验 蹒跚学步的孩子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，约三分之二的奖学金期限)，并进行行为 在杜克大学的实验(约占奖学金期限的三分之一)。这种多机构的设置将 允许学员与具有专业知识、设备和技能的指导团队一起工作 实现项目目标所需的设施，特别是复杂的语言建模技术 学习(麻省理工学院利维博士)和评估幼儿语言知识的实验技术 (伯格森和托马塞洛博士，杜克)导师、实验室和机构的这种组合是完美的 适合提供必要的培训，为申请人成为终身教职做好准备，同时 回答关键的未解决的研究问题。