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Lexical leverage: Category knowledge boosts real-time novel word recognition in two-year- olds

机译:词汇能力:类别知识可促进两岁儿童的实时新颖单词识别

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摘要

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.
机译:最近的研究表明,婴儿往往会在词汇表中添加与其他已知单词在语义上相关的单词,尽管尚不清楚为什么会出现这种模式。在本文中,我们探讨了实时解释新颖的标签-对象映射时,婴儿是否能够利用其现有的词汇和语义知识。我们最初确定的分类领域是,各个24个月大婴儿的知识水平相对较高和较低,而与总词汇量无关。接下来,我们在这些较高和较低的知识领域中教给婴儿新颖的单词,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而变化。尽管我们的参与者在我们的任务中成功获得了新颖的标签-对象映射,但婴儿实时识别这些单词的方式存在重要差异。即,婴儿表现出对高(相对于低)领域知识单词的更可靠的识别。这些发现表明,密集的语义结构有助于早期单词学习和实时新颖单词识别。

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