Lexical leverage: category knowledge boosts real-time novel word recognition in 2-year-olds.
Lexical leverage: category knowledge boosts real-time novel word recognition in 2-year-olds.
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DOI：
10.1111/desc.12343
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发表时间：
2016-11
影响因子：
3.7
通讯作者：
Elman JL
中科院分区：
文献类型：
--
作者：
Borovsky A;Ellis EM;Evans JL;Elman JL
最近的研究表明，婴儿倾向于在他们的词汇中添加与其他已知单词语义相关的单词，尽管还不清楚为什么会出现这种模式。在本文中，我们探讨婴儿是否利用他们现有的词汇和语义知识时，解释新的标签对象映射实时。我们最初确定的范畴域的个人24个月大的婴儿有相对较高和较低的知识水平，无论整体词汇量。接下来，我们教婴儿在这些较高和较低的知识领域的新单词，然后询问他们随后对这些项目的实时识别是否随其类别知识的变化而变化。虽然我们的参与者在我们的任务中成功地获得了新颖的标签-对象映射，但婴儿在真实的时间内识别这些单词的方式存在重要差异。也就是说，婴儿表现出更强大的识别高（与低）域知识的话。这些发现表明，密集的语义结构有利于早期的单词学习和实时的新单词识别。
Recent research suggests that infants tend to add words to their vocabulary that are semantically related to other known words, though it is not clear why this pattern emerges. In this paper, we explore whether infants to leverage their existing vocabulary and semantic knowledge when interpreting novel label-object mappings in real-time. We initially identified categorical domains for which individual 24-month-old infants have relatively higher and lower levels of knowledge, irrespective of overall vocabulary size. Next, we taught infants novel words in these higher and lower knowledge domains and then asked if their subsequent real-time recognition of these items varied as a function of their category knowledge. While our participants successfully acquired the novel label -object mappings in our task, there were important differences in the way infants recognized these words in real time. Namely, infants showed more robust recognition of high (vs. low) domain knowledge words. These findings suggest that dense semantic structure facilitates early word learning and real-time novel word recognition.