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Lexical category acquisition via nonadjacent dependencies in context: Evidence of developmental change and individual differences.

机译:通过上下文中不相邻的依存关系获得词汇类别:发展变化和个体差异的证据。

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摘要

Lexical categories like noun and verb are foundational to language acquisition, but these categories do not come neatly packaged for the infant language learner. Some have proposed that infants can begin to solve this problem by tracking the frequent nonadjacent word (or morpheme) contexts of these categories. However, nonadjacent relationships that frame categories contain reliable adjacent relationships making the type of context (adjacent or nonadjacent) used for category acquisition unclear. In addition, previous research suggests that infants show learning of adjacent dependencies earlier than learning of nonadjacent dependencies and that the learning of nonadjacent word relationships is affected by the intervening information (how informative it is and how familiar it is). Together these issues raise the question of whether the type of context used for category acquisition changes as a function of development. To address this question, infants ages 13, 15, and 18 months were exposed to an artificial language containing adjacent and nonadjacent information that predicted a category. Infants were then tested to determine whether they 1) detected the category using adjacent information 2) only detected the nonadjacent dependency, with no categorization, or 3) detected both the nonadjacent relationship and the category. The results showed high individual variability in the youngest age group with a gradual convergence towards detecting the category and the associated environments by 18 months. These findings suggest that both adjacent and nonadjacent information may be used at early stages in category acquisition. The results reveal a dynamic picture of how infants use distributional information for category acquisition and support a developmental shift consistent with previous infant studies examining dependencies between words.
机译:名词和动词之类的词汇类别是语言习得的基础,但是对于婴儿语言学习者而言,这些类别的包装并不整齐。一些人提出,婴儿可以通过跟踪这些类别中频繁出现的不相邻词(或语素)的语境来解决这个问题。但是,框架类别的不相邻关系包含可靠的相邻关系,因此不清楚用于类别获取的上下文类型(相邻还是不相邻)。另外,先前的研究表明,婴儿比不相邻的依赖者学习早于相邻依赖的学习,并且不相邻的单词关系的学习受中间信息的影响(信息的丰富程度和熟悉程度)。这些问题共同提出了一个问题,即用于类别获取的上下文类型是否随发展而变化。为了解决这个问题,将13、15和18个月的婴儿暴露于一种人工语言,其中包含预测类别的相邻且不相邻的信息。然后对婴儿进行测试,以确定他们是否1)使用相邻信息检测到类别2)仅检测到不相邻的依存关系(没有分类),或3)同时检测到不相邻的关系和类别。结果显示,在最年轻的年龄组中,个体差异很大,并且在18个月之前逐渐趋向于检测类别和相关环境。这些发现表明,相邻和不相邻的信息都可以在类别获取的早期阶段使用。结果揭示了婴儿如何使用分布信息进行类别获取并支持与以往的婴儿研究词之间的依存关系一致的发展变化的动态图景。

著录项

  • 作者

    Sandoval, Michelle.;

  • 作者单位

    The University of Arizona.;

  • 授予单位 The University of Arizona.;
  • 学科 Psychology Developmental.;Psychology Cognitive.;Language Linguistics.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 102 p.
  • 总页数 102
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:53:22

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