In this paper we describe a completely automatic algorithm that builds multiple pronunciation word models by expanding baseform pronunciations with a set of candidate phonological rules. We show how to train the probabilities of these phonological rules, and how to use these probabilities to assign pronunciation probabilities to words not seen in the training corpus. The algorithm wg propose is an instance of the class of techniques we call Exploratory Computational Phonology.