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迈向言语监测的新模式。

Towards a New Model of Verbal Monitoring.

作者信息

Gauvin Hanna S, Hartsuiker Robert J

机构信息

Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, NL.

School of Psychology and Counselling, Queensland University of Technology, Brisbane, QLD, AU.

出版信息

J Cogn. 2020 Sep 3;3(1):17. doi: 10.5334/joc.81.

DOI:10.5334/joc.81
PMID:32944680
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7473241/
Abstract

As all human activities, verbal communication is fraught with errors. It is estimated that humans produce around 16,000 words per day, but the word that is selected for production is not always correct and neither is the articulation always flawless. However, to facilitate communication, it is important to limit the number of errors. This is accomplished via the verbal monitoring mechanism. A body of research over the last century has uncovered a number of properties of the mechanisms at work during verbal monitoring. Over a dozen routes for verbal monitoring have been postulated. However, to date a complete account of verbal monitoring does not exist. In the current paper we first outline the properties of verbal monitoring that have been empirically demonstrated. This is followed by a discussion of current verbal monitoring models: the perceptual loop theory, conflict monitoring, the hierarchical state feedback control model, and the forward model theory. Each of these models is evaluated given empirical findings and theoretical considerations. We then outline lacunae of current theories, which we address with a proposal for a new model of verbal monitoring for production and perception, based on conflict monitoring models. Additionally, this novel model suggests a mechanism of how a detected error leads to a correction. The error resolution mechanism proposed in our new model is then tested in a computational model. Finally, we outline the advances and predictions of the model.

摘要

与所有人类活动一样,言语交流也充满了错误。据估计,人类每天会说出约16000个单词,但所选择说出的单词并不总是正确的,发音也并非总是完美无缺。然而,为了便于交流,限制错误数量很重要。这是通过言语监测机制来实现的。上个世纪的一系列研究揭示了言语监测过程中起作用的机制的一些特性。已经提出了十几种言语监测途径。然而,迄今为止,还没有对言语监测的完整描述。在当前的论文中,我们首先概述已通过实证证明的言语监测特性。接下来讨论当前的言语监测模型:感知循环理论、冲突监测、分层状态反馈控制模型和前向模型理论。根据实证研究结果和理论考量对这些模型逐一进行评估。然后我们概述当前理论的不足之处,并基于冲突监测模型提出一个用于言语产出和感知监测的新模型来加以解决。此外,这个新模型还提出了一种检测到的错误如何导致纠正的机制。我们新模型中提出的错误解决机制随后在一个计算模型中进行了测试。最后,我们概述该模型的进展和预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/1a165d7cb728/joc-3-1-81-g7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/6e66361f2e64/joc-3-1-81-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/beeabe0e6c9f/joc-3-1-81-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/421c656028a6/joc-3-1-81-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/b4fc50b7d0b3/joc-3-1-81-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/e1c4d9cf884e/joc-3-1-81-g5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/e63f094926e5/joc-3-1-81-g6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/1a165d7cb728/joc-3-1-81-g7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/6e66361f2e64/joc-3-1-81-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/beeabe0e6c9f/joc-3-1-81-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/421c656028a6/joc-3-1-81-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/b4fc50b7d0b3/joc-3-1-81-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/e1c4d9cf884e/joc-3-1-81-g5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/e63f094926e5/joc-3-1-81-g6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf68/7473241/1a165d7cb728/joc-3-1-81-g7.jpg

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