Correlation versus prediction in children's word learning: Cross-linguistic evidence and simulations
Correlation versus prediction in children's word learning: Cross-linguistic evidence and simulations
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DOI：
10.1515/langcog.2009.010
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发表时间：
2009-06-01
影响因子：
1.8
通讯作者：
Gasser, Michael
中科院分区：
文献类型：
--
作者：
Colunga, Eliana;Smith, Linda B.;Gasser, Michael
离散的个体对象和连续的实体之间的本体论区别，以及这种区别在不同语言中的表达方式，一直是研究语言与思想之间关系的肥沃领域。在本文中，我们将模拟和跨语言单词学习任务结合起来，以深入了解单词学习中涉及的学习机制的本质。首先，我们通过在神经网络中实现的两种学习任务——预测和关联，研究了不同的相关结构对新泛化的影响。其次，我们观察了说英语和西班牙语的2-3岁儿童的小说名词概括，发现计数/质量句法对西班牙语儿童的小说名词概括的影响比对说英语儿童的小说名词概括的影响更大，这与预测网络一致。研究结果表明，决定语言线索学习方式的不仅仅是不同语言线索的相关结构，还有它们所涉及的具体学习机制和任务。
The ontological distinction between discrete individuated objects and continuous substances, and the way this distinction is expressed in different languages has been a fertile area for examining the relation between language and thought. In this paper we combine simulations and a cross-linguistic word learning task as a way to gain insight into the nature of the learning mechanisms involved in word learning. First, we look at the effect of the different correlational structures on novel generalizations with two kinds of learning tasks implemented in neural networks-prediction and correlation. Second, we look at English-and Spanish-speaking 2-3-year-olds' novel noun generalizations, and find that count / mass syntax has a stronger effect on Spanish-than on English-speaking children's novel noun generalizations, consistent with the predicting networks. The results suggest that it is not just the correlational structure of different linguistic cues that will determine how they are learned, but the specific learning mechanism and task in which they are involved.