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.

At least 3 different types of computational model have been shown to account for various facets of both normal and impaired single word reading: (a) the connectionist triangle model, (b) the dual-route cascaded model, and (c) the connectionist dual process model. Major strengths and weaknesses of these models are identified. In the spirit of nested incremental modeling, a new connectionist dual process model (the CDPϩ model) is presented. This model builds on the strengths of 2 of the previous models while eliminating their weaknesses. Contrary to the dual-route cascaded model, CDPϩ is able to learn and produce graded consistency effects. Contrary to the triangle and the connectionist dual process models, CDPϩ accounts for serial effects and has more accurate nonword reading performance. CDPϩ also beats all previous models by an order of magnitude when predicting individual item-level variance on large databases. Thus, the authors show that building on existing theories by combining the best features of previous models-a nested modeling strategy that is commonly used in other areas of science but often neglected in psychology-results in better and more powerful computational models.

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It is hypothesized that written languages differ in the preferred grain size of units that emerge during reading acquisition. Smaller units (graphemes, phonemes) are thought to play a dominant role in relatively consistent orthographies (e.g., German), whereas larger units (bodies, rhymes) are thought to be more important in relatively inconsistent orthographies (e.g., English). This hypothesis was tested by having native English and German speakers read identical words and nonwords in their respective languages (zoo-Zoo, sand-Sand, etc.). Although the English participants exhibited stronger body-rhyme effects, the German participants exhibited a stronger length effect for words and nonwords. Thus, identical items were processed differently in different orthographies. These results suggest that orthographic consistency determines not only the relative contribution of orthographic versus phonological codes within a given orthography; but also the preferred grain size of units that are likely to be functional during reading.