A Bayesian Model of Natural Language Phonology: Generating Alternations from Underlying Forms

Abstract

A stochastic approach to learning phonology. The model presented captures 7--15% more phonologically plausible underlying forms than a simple majority solution, because it prefers "pure" alternations. It could be useful in cases where an approximate solution is needed, or as a seed for more complex models. A similar process could be involved in some stages of child language acquisition; in particular, early learning of phonotactics.