Much of the power of neural network modeling for language use and acquisition derives from a reliance on statistical regularities implicit in the phonological properties of words. Researchers have devised several methods for representing the phonology of words, but these methods are often either unable to represent realistically sized lexicons or inadequate in the ways they represent individual words. In this paper, we present a new phonological pattern generator (PatPho) that allows connectionist modelers to derive accurate phonological representations of the English lexicon. PatPho not only generates phonological patterns that can scale up to realistically sized lexicons, but also accurately and parsi moniously captures the similarity structures of the phonology of monosyllabic and multi syllabic words.
A detailed description of the database is available in the following papers:
- Li, P., & MacWhinney, B. (2002). PatPho: A phonological pattern generator for neural networks. Behavior Research Methods, Instruments, and Computers, 34, 408-415.
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