from Part II - Cross-Linguistic Perspectives on Developmental Dyslexia
Published online by Cambridge University Press: 27 September 2019
Computational models of reading have played an important role in theorizing about developmental dyslexia. In particular, simulations of how children learn to read, based on Parallel Distributed Processing (PDP) principles, such as the triangle model (Seidenberg & McClelland, 1989) have been influential, because they hold the promise of explaining complex phenomena as emerging from a relatively simple set of assumptions. For example, Harm and Seidenberg (1999) demonstrated how lower-level perceptual difficulties that interfere with the formation of phonological categories can give rise to specific deficits observed in phonological dyslexia in English. The theory behind the triangle model is that reading skill emerges as a result of statistically driven learning of the mappings among the written and spoken forms of words and their meanings. At the computational level of analysis, this provides the basis for a universal model of reading across languages (e.g. Frost, 2012).
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