University of California, San Diego.
Cogn Sci. 2020 Nov;44(11):e12899. doi: 10.1111/cogs.12899.
Children show a remarkable degree of consistency in learning some words earlier than others. What patterns of word usage predict variations among words in age of acquisition? We use distributional analysis of a naturalistic corpus of child-directed speech to create quantitative features representing natural variability in word contexts. We evaluate two sets of features: One set is generated from the distribution of words into frames defined by the two adjacent words. These features primarily encode syntactic aspects of word usage. The other set is generated from non-adjacent co-occurrences between words. These features encode complementary thematic aspects of word usage. Regression models using these distributional features to predict age of acquisition of 656 early-acquired English words indicate that both types of features improve predictions over simpler models based on frequency and appearance in salient or simple utterance contexts. Syntactic features were stronger predictors of children's production than comprehension, whereas thematic features were stronger predictors of comprehension. Overall, earlier acquisition was predicted by features representing frames that select for nouns and verbs, and by thematic content related to food and face-to-face play topics; later acquisition was predicted by features representing frames that select for pronouns and question words, and by content related to narratives and object play.
儿童在学习某些词汇时表现出惊人的一致性，有些词汇比其他词汇更早被习得。哪些词汇使用模式可以预测习得年龄的变化？我们使用自然语料库中儿童导向话语的分布分析来创建定量特征，以表示词汇上下文的自然变化。我们评估了两组特征：一组是根据两个相邻单词定义的框架，从单词分布中生成的特征。这些特征主要编码词汇使用的句法方面。另一组是从单词之间的非相邻共现生成的特征。这些特征编码词汇使用的互补主题方面。使用这些分布特征的回归模型来预测 656 个早期习得的英语单词的习得年龄表明，这两种类型的特征都比基于频率和在显著或简单的话语上下文中出现的简单模型更能提高预测能力。句法特征对儿童的产生能力预测比理解能力预测更准确，而主题特征对理解能力预测更准确。总体而言，选择名词和动词的框架特征以及与食物和面对面游戏主题相关的主题内容预测了较早的习得，而选择代词和疑问词的框架特征以及与叙事和物体游戏相关的内容预测了较晚的习得。
