DRC: a dual route cascaded model of visual word recognition and reading aloud.
DRC: a dual route cascaded model of visual word recognition and reading aloud.
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DOI：
10.1037/0033-295x.108.1.204
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发表时间：
2001
影响因子：
5.4
通讯作者：
M. Coltheart;K. Rastle;C. Perry;R. Langdon;J. Ziegler
中科院分区：
文献类型：
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作者：
M. Coltheart;K. Rastle;C. Perry;R. Langdon;J. Ziegler
本文介绍了双路由级联 (DRC) 模型，这是一种视觉单词识别和朗读的计算模型。 DRC 是双路径阅读理论的计算实现，并且是唯一可以执行阅读研究中最常用的 2 个任务的阅读计算模型：词汇决策和朗读。对于这两项任务，作者表明，影响人类延迟的各种变量以完全相同的方式影响 DRC 模型的延迟。 DRC 模型模拟了其他阅读计算模型无法模拟的许多此类效果，但似乎没有任何其他当前阅读计算模型可以模拟但 DRC 模型不能模拟的效果。作者得出的结论是，DRC 模型是现有阅读计算模型中最成功的。
This article describes the Dual Route Cascaded (DRC) model, a computational model of visual word recognition and reading aloud. The DRC is a computational realization of the dual-route theory of reading, and is the only computational model of reading that can perform the 2 tasks most commonly used to study reading: lexical decision and reading aloud. For both tasks, the authors show that a wide variety of variables that influence human latencies influence the DRC model's latencies in exactly the same way. The DRC model simulates a number of such effects that other computational models of reading do not, but there appear to be no effects that any other current computational model of reading can simulate but that the DRC model cannot. The authors conclude that the DRC model is the most successful of the existing computational models of reading.