Vitevitch Michael S, Chan Kit Ying, Goldstein Rutherford
Department of Psychology, University of Kansas, United States.
Department of Psychology, University of Kansas, United States.
Cogn Psychol. 2014 Feb;68:1-32. doi: 10.1016/j.cogpsych.2013.10.002. Epub 2013 Nov 20.
Previous network analyses of the phonological lexicon (Vitevitch, 2008) observed a web-like structure that exhibited assortative mixing by degree: words with dense phonological neighborhoods tend to have as neighbors words that also have dense phonological neighborhoods, and words with sparse phonological neighborhoods tend to have as neighbors words that also have sparse phonological neighborhoods. Given the role that assortative mixing by degree plays in network resilience, we examined instances of real and simulated lexical retrieval failures in computer simulations, analysis of a slips-of-the-ear corpus, and three psycholinguistic experiments for evidence of this network characteristic in human behavior. The results of the various analyses support the hypothesis that the structure of words in the mental lexicon influences lexical processing. The implications of network science for current models of spoken word recognition, language processing, and cognitive psychology more generally are discussed.
先前对语音词汇的网络分析(维特维奇,2008年)观察到一种类似网络的结构,这种结构呈现出度的同配混合:语音邻域密集的单词倾向于以同样具有密集语音邻域的单词作为邻居,而语音邻域稀疏的单词倾向于以同样具有稀疏语音邻域的单词作为邻居。鉴于度的同配混合在网络弹性中所起的作用,我们在计算机模拟、对耳误语料库的分析以及三项心理语言学实验中,研究了真实和模拟的词汇检索失败实例,以寻找人类行为中这种网络特征的证据。各种分析结果支持了心理词库中单词结构影响词汇加工的假设。本文还讨论了网络科学对当前口语单词识别、语言加工以及更广泛的认知心理学模型的影响。