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在心理词典中识别语音主干。

Identifying the phonological backbone in the mental lexicon.

机构信息

University of Kansas, Lawrence, KS, United States of America.

出版信息

PLoS One. 2023 Jun 23;18(6):e0287197. doi: 10.1371/journal.pone.0287197. eCollection 2023.

Abstract

Previous studies used techniques from network science to identify individual nodes and a set of nodes that were "important" in a network of phonological word-forms from English. In the present study we used a network simplification process-known as the backbone-that removed redundant edges to extract a subnetwork of "important" words from the network of phonological word-forms. The backbone procedure removed 68.5% of the edges in the original network to extract a backbone with a giant component containing 6,211 words. We compared psycholinguistic and network measures of the words in the backbone to the words that did not survive the backbone extraction procedure. Words in the backbone occurred more frequently in the language, were shorter in length, were similar to more phonological neighbors, and were closer to other words than words that did not survive the backbone extraction procedure. Words in the backbone of the phonological network might form a "kernel lexicon"-a small but essential set of words that allows one to communicate in a wide-range of situations-and may provide guidance to clinicians and researchers on which words to focus on to facilitate typical development, or to accelerate rehabilitation efforts. The backbone extraction method may also prove useful in other applications of network science to the speech, language, hearing and cognitive sciences.

摘要

先前的研究运用网络科学的技术,从英语的音位词汇网络中识别出个体节点和一组“重要”节点。在本研究中,我们使用了一种网络简化过程——称为骨干网络——去除冗余的边,从音位词汇网络中提取出“重要”单词的子网。骨干程序去除了原始网络中 68.5%的边,提取出一个包含 6,211 个单词的巨分量骨干网络。我们比较了骨干网络中的单词和未通过骨干提取过程的单词的心理语言和网络测量值。骨干网络中的单词在语言中出现的频率更高,长度更短,与更多的语音邻居相似,并且与未通过骨干提取过程的单词相比,与其他单词更接近。音位网络的骨干网络中的单词可能形成一个“核心词汇表”——一个小而必要的单词集,它允许人们在广泛的情况下进行交流,并为临床医生和研究人员提供指导,帮助他们专注于哪些单词,以促进典型的发展,或加速康复工作。骨干网络提取方法也可能在网络科学的其他应用中对言语、语言、听力和认知科学领域有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/020a/10289336/3050cfc666af/pone.0287197.g001.jpg

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