A novel approach to inferring letter-phoneme correspondences

An inference algorithm to obtain letter-phoneme correspondences for English using image-processing techniques is described. The main idea of the inference algorithm is to construct a table of association indices. The table is regarded as an image and image-processing algorithms are use to derive letter-phoneme correspondences. The advantages of the technique are that the association index has a theoretical basis in terms of modeling spelling and pronunciation as a homogeneous Markov chain, computational demand is low, and the inference process is not dependent on the ordering of the sample. The authors have implemented both a thresholding and a minimum spanning tree technique to derive correspondences. Illustrative examples are given for each technique