When cues converge: multiple regularities in language acquisition

当线索汇聚时：语言习得的多重规律

• 批准号: 7488931
• 负责人: Sarah Devi Sahni
• 金额: $ 3.15万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7488931
• 关键词: Adherence; Affect; Behavioral; Body of uterus; Child; Complex; Computer Simulation; Computing Methodologies; Cues; Depth; Educational process of instructing; Environment; Face; Future; Goals; Grant; Infant; Label; Laboratories; Language; Language Delays; Language Development; Lead; Learning; Linguistics; Machine Learning; Maps; Modeling; Natural Language Processing; Neural Network Simulation; Numbers; Pattern; Probability; Process; Public Health; Research; Research Personnel; Research Project Grants; Role; Speech; Stress; System; Testing; Vocabulary; Weight; Work; design; disability; experience; interest; lexical; novel; research study; simulation; skills; sound; statistics; tool; treatment planning

DESCRIPTION (provided by applicant): The goal of this research project is to employ behavioral and computational methods to better understand how infants use multiple regularities when learning language. Many researchers have posited that infants use statistical learning mechanisms to extract these regularities. However, the majority of this work focuses on infants' abilities to exploit a single regularity. In their natural environment, infants receive input that contains many overlapping regularities of varying consistency. Little research has focused on how infants process this type of input. In order to make use of the cues available in natural input, infants must be able to exploit these overlapping probabilistic regularities. The first aim of this grant is to explore how infants use multiple regularities to find words in fluent speech. By 9 months, infants are able to robustly use both lexical stress and sequential statistics to segment words. However, prior research has focused on how infants use these regularities in isolation, or how weighting of the cues changes developmentally. We hypothesize that infants can use these cues for word segmentation when they are probabilistic and overlapping, as they are in natural languages such as English. The second aim is to investigate the effect of multiple regularities on word learning. As a child's vocabulary grows, regularities arise among the labels and referents they know, as well as within the mappings between labels and referents. These regularities may affect the acquisition of new words. However, their potential role in subsequent word learning has not been carefully explored. Using computational models, we can examine these issues by carefully controlling regularities that exist within a vocabulary and by exploring how different types of regularities may affect word learning. These models can lead to a deeper understanding of these processing mechanisms and to novel predictions, which can then be tested in behavioral experiments. Public Health Interests: The goal of this research is to better understand how typically developing infants learn language - in particular, how they use the many patterns that exist in natural languages to do so. The ability to make use of multiple regularities likely affects infants' skills at language learning. By better understanding how this process unfolds in typically developing infants, researchers will be able to investigate how children with language delays and disabilities may differ in their ability to integrate multiple cues. In the future, this information will be useful for developing treatment plans.

描述（由申请人提供）：本研究项目的目标是采用行为和计算方法，以更好地了解婴儿在学习语言时如何使用多种语言。许多研究人员认为，婴儿使用统计学习机制来提取这些信息。然而，这项工作的大部分集中在婴儿的能力，利用一个单一的规律。在他们的自然环境中，婴儿接受的输入包含许多重叠的不同一致性的信息。很少有研究关注婴儿如何处理这种类型的输入。为了利用自然输入中的线索，婴儿必须能够利用这些重叠的概率信息。这项资助的第一个目的是探索婴儿如何使用多个词在流利的讲话中找到单词。到9个月时，婴儿能够稳健地使用词汇重音和顺序统计来分割单词。然而，之前的研究集中在婴儿如何孤立地使用这些线索，或者这些线索的权重如何随着发育而变化。我们假设，婴儿可以使用这些线索时，他们是概率和重叠的分词，因为他们是在自然语言，如英语。第二个目的是探讨多项任务对词汇学习的影响。随着孩子词汇量的增长，他们会在他们所知道的标签和所指对象之间以及标签和所指对象之间的映射中产生联想。这些错误可能会影响新单词的习得。然而，它们在随后的单词学习中的潜在作用尚未被仔细探索。使用计算模型，我们可以通过仔细控制词汇中存在的重复和探索不同类型的重复如何影响单词学习来研究这些问题。这些模型可以导致对这些处理机制的更深入理解，并产生新的预测，然后可以在行为实验中进行测试。 公共卫生利益：这项研究的目的是更好地了解发育中的婴儿是如何学习语言的，特别是他们如何使用自然语言中存在的许多模式来学习语言。使用多种语言的能力可能会影响婴儿的语言学习技能。通过更好地了解这一过程如何在典型的发育中的婴儿中展开，研究人员将能够调查语言延迟和残疾儿童在整合多种线索的能力方面可能存在的差异。将来，这些信息将有助于制定治疗计划。