Harm, Michael W.

Division of Labor in a Computational Model of Visual Word Recognition

Ph.D. Thesis, August 1998, University of Southern California

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Abstract: How do we compute the meanings of written words? For decades, the basic mechanisms underlying visual word recognition have remained controversial. The intuitions of educators and policy makers, and the existing empirical evidence have resulted in contradictory conclusions, particularly about the role of the sound structure of language (phonology) in word recognition. To explore the relative contributions of phonological and direct information in word recognition, a large scale connectionist model of visual word recognition was created containing orthographic, semantic and phonological representations. The behavior of the model is analyzed and explained in terms of redundant representations, the development of dynamic attractors in representational space, the time course of activation and processing within such networks, and demands of the reading task itself. The different patterns of results that have been obtained in previous behavioral studies are explained by appeal to stimulus composition and properties of a common experimental paradigm. A unified explanation of a wide range of empirical phenomena is presented.


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