READING EXCEPTION WORDS AND PSEUDOWORDS - ARE 2 ROUTES REALLY NECESSARY

This paper describes simulation experiments demonstrating that a unitary processing system in the form of a connectionist network is capable of learning to read exception words and pronounceable nonwords aloud. We trained such a network on the 3000 word corpus used by Seidenberg and McClelland (1989). After training, the network was able to read over 99% of the training corpus correctly. When tested on the lists of pronounceable nonwords used in several experiments, its accuracy was closely comparable to that displayed by human subjects. The work addresses the ongoing debate about the nature of the mechanisms that are used in reading words aloud. One view, defended most recently by Coltheart, Curtis, Atkins, and Haller (1993), states that adequate performance on both pronounceable nonwords and exception words depends on the use of two separate mechanisms, one that applies rules of grapheme phoneme correspondence and another that retrieves pronunciations specific to particular familiar words. An alternative view, expressed by Seidenberg and McClelland, is that a single system may be capable of learning to read both kinds of letter strings. The work relates more generally to the ongoing debate about the nature of the processing systems underlying human language use. The question is, should these systems be viewed as systems that learn and apply an explicit system of rules, augmented where necessary with an explicit enumeration of exceptions; or should these systems be viewed instead as connectionist systems that gradually develop sensitivity to the structure inherent in the mapping they are asked to learn, through a gradual learning procedure. The connectionist approach has considerable appeal, because it accounts for the fact that regularity is a graded phenomenon and for the fact that human language users are sensitive to these gradations. In the domain of spelling-to-sound translation, Glushko (1979) was the first to emphasize that in fact the crucial variable for word pronunciation tasks is not regularity, but degree of consistency of the spelling-to-sound correspondences exhibited by one word to the correspondences exhibited by its neighbors. Since Glushko’s work it has been clearly established that the more consistent a word’s spelling to sound correspondences are