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视觉词汇识别模型。

Models of visual word recognition.

机构信息

Medical Research Council Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge CB2 7EF, UK.

出版信息

Trends Cogn Sci. 2013 Oct;17(10):517-24. doi: 10.1016/j.tics.2013.08.003. Epub 2013 Sep 4.

Abstract

Reading is a complex process that draws on a remarkable number of diverse perceptual and cognitive processes. In this review, I provide an overview of computational models of reading, focussing on models of visual word recognition-how we recognise individual words. Early computational models had 'toy' lexicons, could simulate only a narrow range of phenomena, and frequently had fundamental limitations, such as being able to handle only four-letter words. The most recent models can use realistic lexicons, can simulate data from a range of tasks, and can process words of different lengths. These models are the driving force behind much of the empirical work on reading. I discuss how the data have guided model development and, importantly, I also provide guidelines to help interpret and evaluate the contribution the models make to our understanding of how we read.

摘要

阅读是一个复杂的过程,涉及到许多不同的感知和认知过程。在这篇综述中,我提供了阅读的计算模型概述,重点是视觉单词识别模型——我们如何识别单个单词。早期的计算模型具有“玩具”词汇表,只能模拟很窄的范围的现象,并且经常存在根本性的限制,例如只能处理四个字母的单词。最近的模型可以使用现实的词汇表,可以模拟来自各种任务的数据,并且可以处理不同长度的单词。这些模型是阅读领域的大部分实证工作的推动力。我讨论了数据如何指导模型的开发,并且重要的是,我还提供了指导方针,以帮助解释和评估模型对我们理解阅读方式的贡献。

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