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并行激活模型中的语言生成与预测

Language Production and Prediction in a Parallel Activation Model.

作者信息

Pickering Martin J, Strijkers Kristof

机构信息

Department of Psychology, University of Edinburgh.

Laboratoire de Parole et Langage (LPL), Aix-Marseille Université & CNRS.

出版信息

Top Cogn Sci. 2024 Nov 22. doi: 10.1111/tops.12775.

Abstract

Standard models of lexical production assume that speakers access representations of meaning, grammar, and different aspects of sound in a roughly sequential manner (whether or not they admit cascading or interactivity). In contrast, we review evidence for a parallel activation model in which these representations are accessed in parallel. According to this account, word learning involves the binding of the meaning, grammar, and sound of a word into a single representation. This representation is then activated as a whole during production, and so all linguistic components are available simultaneously. We then note that language comprehension involves extensive use of prediction and argue that comprehenders use production mechanisms to determine (roughly) what they would say next if they were speaking. So far, theories of prediction-by-production have assumed sequential lexical production. We therefore reinterpret such evidence in terms of parallel lexical production.

摘要

词汇生成的标准模型假定,说话者以大致顺序的方式获取意义、语法以及声音不同方面的表征(无论他们是否承认存在级联或交互作用)。相比之下,我们回顾了支持并行激活模型的证据,在该模型中,这些表征是并行获取的。根据这一观点,词汇学习涉及将一个单词的意义、语法和声音绑定到一个单一的表征中。这个表征在生成过程中作为一个整体被激活,因此所有语言成分可同时使用。然后我们指出,语言理解大量运用了预测,并认为理解者使用生成机制来大致确定如果他们在说话接下来会说什么。到目前为止,通过生成进行预测的理论假定了顺序性的词汇生成。因此,我们根据并行词汇生成重新解释此类证据。

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