Jones Gary
Nottingham Trent University, UK.
Cognition. 2016 Aug;153:79-88. doi: 10.1016/j.cognition.2016.04.017. Epub 2016 May 4.
Nonword repetition (NWR) is highly predictive of vocabulary size, has strong links to language and reading ability, and is a clinical marker of language impairment. However, it is unclear what processes provide major contributions to NWR performance. This paper presents a computational model of NWR based on Chunking Lexical and Sub-lexical Sequences in Children (CLASSIC) that focuses on the child's exposure to language when learning lexical phonological knowledge. Based on language input aimed at 2-6year old children, CLASSIC shows a substantial fit to children's NWR performance for 6 different types of NWR test across 6 different NWR studies that use children of various ages from 2;1 to 6;1. Furthermore, CLASSIC's repetitions of individual nonwords correlate significantly with children's repetitions of the same nonwords, NWR performance shows strong correlations to vocabulary size, and interaction effects seen in the model are consistent with those found in children. Such a fit to the data is achieved without any need for developmental parameters, suggesting that between the ages of two and six years, NWR performance measures the child's current level of linguistic knowledge that arises from their exposure to language over time and their ability to extract lexical phonological knowledge from that exposure.
非词重复(NWR)对词汇量具有高度预测性,与语言和阅读能力有紧密联系,并且是语言障碍的一个临床指标。然而,尚不清楚哪些过程对NWR表现有主要贡献。本文提出了一个基于儿童词汇和次词汇序列组块(CLASSIC)的NWR计算模型,该模型关注儿童在学习词汇语音知识时接触语言的情况。基于针对2至6岁儿童的语言输入,CLASSIC在6项不同的NWR研究中,对6种不同类型的NWR测试中不同年龄(从2;1到6;1)儿童的NWR表现有显著拟合。此外,CLASSIC对单个非词的重复与儿童对相同非词的重复显著相关,NWR表现与词汇量有很强的相关性,并且模型中观察到的交互效应与在儿童中发现的一致。在无需任何发展参数的情况下就能实现对数据的这种拟合,这表明在两岁至六岁之间,NWR表现衡量了儿童当前的语言知识水平,这种水平源于他们长期接触语言以及从这种接触中提取词汇语音知识的能力。