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内隐学习两种人工语法。

Implicit learning of two artificial grammars.

机构信息

Lyon Neuroscience Research Center, Auditory Cognition and Psychoacoustics Team, Bron, France.

CNRS, UMR5292, INSERM, U1028, Bron, France.

出版信息

Cogn Process. 2021 Feb;22(1):141-150. doi: 10.1007/s10339-020-00996-2. Epub 2020 Oct 6.

Abstract

This study investigated the implicit learning of two artificial systems. Two finite-state grammars were implemented with the same tone set (leading to short melodies) and played by the same timbre in exposure and test phases. The grammars were presented in separate exposure phases, and potentially acquired knowledge was tested with two experimental tasks: a grammar categorization task (Experiment 1) and a grammatical error detection task (Experiment 2). Results showed that participants were able to categorize new items as belonging to one or the other grammar (Experiment 1) and detect grammatical errors in new sequences of each grammar (Experiment 2). Our findings suggest the capacity of intra-modal learning of regularities in the auditory modality and based on stimuli that share the same perceptual properties.

摘要

本研究考察了两个人工系统的内隐学习。两个有限状态语法使用相同的音高集(产生短旋律)实现,并在暴露和测试阶段使用相同的音色演奏。语法在单独的暴露阶段呈现,潜在的知识通过两个实验任务进行测试:语法分类任务(实验 1)和语法错误检测任务(实验 2)。结果表明,参与者能够将新项目归类为属于一个或另一个语法(实验 1),并检测每个语法的新序列中的语法错误(实验 2)。我们的发现表明,在听觉模态中基于具有相同感知属性的刺激,能够进行模态内的规则学习。

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