Network Structure Influences Speech Production
Network Structure Influences Speech Production
复制标题
DOI：
10.1111/j.1551-6709.2010.01100.x
复制
发表时间：
2010-05-01
影响因子：
2.5
通讯作者：
Vitevitch, Michael S.
中科院分区：
文献类型：
--
作者：
Chan, Kit Ying;Vitevitch, Michael S.
网络科学提供了一种新的方式来看待认知科学中的老问题，通过研究复杂系统的结构，以及这种结构如何影响处理。在心理语言学的语境中，聚类系数是网络科学中的一个常用度量指标，它是指目标词的语音相邻词之间相互相邻的程度。在语音错误语料库和图片命名任务中考察了聚类系数对口语词产生的影响。语音错误倾向于发生在具有许多互连邻居的单词中（即，聚类系数较高）。此外，表示具有许多互连邻居的单词的图片（即，更高的聚类系数）比表示具有较少互连邻居的单词的图片（即，聚类系数低）。这些研究结果表明，在口语词汇产生过程中，词汇的结构影响着词汇通达的过程。
Network science provides a new way to look at old questions in cognitive science by examining the structure of a complex system, and how that structure might influence processing. In the context of psycholinguistics, clustering coefficient-a common measure in network science-refers to the extent to which phonological neighbors of a target word are also neighbors of each other. The influence of the clustering coefficient on spoken word production was examined in a corpus of speech errors and a picture-naming task. Speech errors tended to occur in words with many interconnected neighbors (i.e., higher clustering coefficient). Also, pictures representing words with many interconnected neighbors (i.e., high clustering coefficient) were named more slowly than pictures representing words with few interconnected neighbors (i.e., low clustering coefficient). These findings suggest that the structure of the lexicon influences the process of lexical access during spoken word production.