An Efficient Way to Learnenglish Grapheme - to - Phoneme Rules

We present an eecient way to learn automatically grapheme-to-phoneme mapping rules for English by using Kohonen's concept of Dynamically Expanding Context. This method constructs rules that are most general in the sense of an explicitly deened speciicity hierarchy. As the hierarchy, we have used the amount of expanding context around the symbol to be transformed , weighted towards the right. To apply this concept to English text-to-speech mapping, we have used the 20008-word corpus provided in the public domain by Sejnowski and Rosenberg, that was also used in the NETTALK-experiments. Phoneme-level mapping accuracies of 91 per cent with data not used in training demonstrate that the Dynamically Expanding Context is able to capture quite eeciently the context-dependent relationships in the corpus.