Learning Communicative Acts in Children's Conversations: A Hidden Topic Markov Model Analysis of the CHILDES Corpora
Learning Communicative Acts in Children's Conversations: A Hidden Topic Markov Model Analysis of the CHILDES Corpora
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DOI：
10.1111/tops.12591
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发表时间：
2021-12-16
影响因子：
3
通讯作者：
Yurovsky, Daniel
中科院分区：
文献类型：
--
作者：
Bergey, Claire;Marshall, Zoe;Yurovsky, Daniel
在他们生命的头几年，孩子们不仅学习他们母语的单词，还学习如何使用它们进行交流。由于对交际意图的手动注释不适用于大型语料库，因此我们对交际行为发展的理解仅限于几个时间点上的少数儿童的案例研究。我们提出了一种基于隐话题马尔可夫模型的自动识别交际行为的方法，并将其应用于Childes数据库中英语学习儿童的会话中。我们首先描述了亲子沟通在发展过程中的质变，然后用我们的方法证明了沟通发展的两个大规模特征：(A)儿童迅速发展出类似父母的沟通行为，他们的学习速度在14个月左右达到顶峰；(B)这段沟通行为的急剧变化时期恰逢父母行为和孩子行为之间的最高可预测性，这表明结构化互动在学习沟通中发挥了作用。
Over their first years of life, children learn not just the words of their native languages, but how to use them to communicate. Because manual annotation of communicative intent does not scale to large corpora, our understanding of communicative act development is limited to case studies of a few children at a few time points. We present an approach to automatic identification of communicative acts using a hidden topic Markov model, applying it to the conversations of English-learning children in the CHILDES database. We first describe qualitative changes in parent-child communication over development, and then use our method to demonstrate two large-scale features of communicative development: (a) children develop a parent-like repertoire of our model's communicative acts rapidly, their learning rate peaking around 14 months of age, and (b) this period of steep repertoire change coincides with the highest predictability between parents' acts and children's, suggesting that structured interactions play a role in learning to communicate.