Abstract

We describe an algorithm to learn word pronunciations from acoustic data. The algorithm jointly optimizes the pronunciation of a word using (a) the acoustic match of this pronunciation to the observed data, and (b) how “linguistically reasonable ” the pronunciation is. Variations of word pronunciations in the recognition dictionary (which was created by linguists), are used to train a model of whether new hypothesized pronunciations are reasonable or not. The algorithm is well-suited for proper name pronunciation learning. Experiments on a corporate name dialing database show 40 % error rate reduction with respect to a letter-to-phone pronunciation engine. 1.

Citations