Learning Pronunciation Rules for English Graphemes Using the Version Space Algorithm

We describe a technique for learning pronunciation rules based on the Version Space algorithm. In particular, we describe how to learn pronunciation rules for a representative subset of the English graphemes. We present a learning procedure called LEP-G.1 (learning to pronounce English graphemes) that learns English pronunciation rules from examples in the form of word-pronunciation pairs. With our approach, we can translate not only English words in dictionaries, but also new words such as tuple, pixel, and deque which are not found in dictionaries. An experiment where LEP-G.1 learned pronunciation rules for 12 graphemes strongly suggests that learning the other possible 52 graphemes in English is feasible.