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音节作为语言交际中信息传递的单位:熵音节切分模型。

Syllable as a unit of information transfer in linguistic communication: The entropy syllable parsing model.

机构信息

Department of Communicative Disorders, University of Alabama, Tuscaloosa, Alabama.

Department of Speech, Language, Hearing Sciences, College of Health and Human Sciences, Purdue University, West Lafayette, Indiana.

出版信息

Wiley Interdiscip Rev Cogn Sci. 2020 Jan;11(1):e1518. doi: 10.1002/wcs.1518. Epub 2019 Sep 10.

Abstract

To understand human language-both spoken and signed-the listener or viewer has to parse the continuous external signal into components. The question of what those components are (e.g., phrases, words, sounds, phonemes?) has been a subject of long-standing debate. We re-frame this question to ask: What properties of the incoming visual or auditory signal are indispensable to eliciting language comprehension? In this review, we assess the phenomenon of language parsing from modality-independent viewpoint. We show that the interplay between dynamic changes in the entropy of the signal and between neural entrainment to the signal at syllable level (4-5 Hz range) is causally related to language comprehension in both speech and sign language. This modality-independent Entropy Syllable Parsing model for the linguistic signal offers insight into the mechanisms of language processing, suggesting common neurocomputational bases for syllables in speech and sign language. This article is categorized under: Linguistics > Linguistic Theory Linguistics > Language in Mind and Brain Linguistics > Computational Models of Language Psychology > Language.

摘要

为了理解人类语言(包括口语和手语),听众或观察者必须将连续的外部信号分解成各个组成部分。这些组成部分是什么(例如,短语、单词、声音、音素?)一直是一个长期存在的争论话题。我们重新构建这个问题,以询问:传入的视觉或听觉信号的哪些特性对于引发语言理解是必不可少的?在这篇综述中,我们从与模态无关的角度评估语言解析现象。我们表明,信号熵的动态变化之间以及信号在音节水平(4-5 Hz 范围)的神经同步之间的相互作用与口语和手语中的语言理解有因果关系。这种与模态无关的语言信号熵音节解析模型为语言处理机制提供了深入的见解,表明在言语和手语中的音节具有共同的神经计算基础。本文属于以下分类:语言学 > 语言理论 语言学 > 语言与心智 语言学 > 语言的计算模型 心理学 > 语言。

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