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语音网络流畅度通过心理搜索识别语音重组。

Phonological network fluency identifies phonological restructuring through mental search.

机构信息

University of Macau, Department of English, Macau S.A.R., China.

Aix-Marseille University, Laboratoire Parole et Langage, Aix-en-Provence, 13100, France.

出版信息

Sci Rep. 2019 Nov 5;9(1):15984. doi: 10.1038/s41598-019-52433-w.

Abstract

We investigated network principles underlying mental search through a novel phonological verbal fluency task. Post exclusion, 95 native-language Mandarin speakers produced as many items that differed by a single lexical tone as possible within one minute. Their verbal productions were assessed according to several novel graded fluency measures, and network science measures that accounted for the structure, cohesion and interconnectedness of lexical items. A multivariate regression analysis of our participants' language backgrounds included their mono- or multi-lingual status, English proficiency, and fluency in other Chinese languages/dialects. Higher English proficiency predicted lower error rates and greater interconnectedness, while higher fluency in other Chinese languages/dialects revealed lower successive similarity and lower network coherence. This inverse relationship between English and other Chinese languages/dialects provides evidence of the restructuring of the phonological mental lexicon.

摘要

我们通过一项新颖的语音词汇流畅性任务研究了心理搜索的网络原则。排除后,95 名母语为普通话的人在一分钟内尽可能多地生成了仅一个声调不同的项目。根据几个新颖的分级流畅性度量标准和网络科学度量标准来评估他们的言语产生情况,这些标准考虑了词汇项目的结构、内聚性和相互连接性。对参与者语言背景的多元回归分析包括他们的单语或多语状态、英语熟练程度以及其他中文语言/方言的流利程度。较高的英语熟练程度预测了较低的错误率和较高的连接性,而其他中文语言/方言的流利程度则显示出较低的连续相似性和较低的网络一致性。英语和其他中文语言/方言之间的这种反比关系提供了语音心理词汇重组的证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c9e/6831682/a084d47cac7d/41598_2019_52433_Fig1_HTML.jpg

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