Graphon: A Comparison of Grapheme-to-phoneme Conversion Performance between an Automated System and Primary Grade Students

Abstract

Grapheme-to-phoneme conversion is a necessary part of reading, whether by an automated system or by children. Automated methods play a key role in text-to-speech and automated speech recognition systems. Children learning to read develop grapheme-to-phoneme (G2P) conversion rules that they use extensively until they build up their orthographic lexicon. Various solutions have been proposed for G2P conversion, each addressing specific problems and evaluated for different languages. In this thesis, I introduce a simple approach to G2P conversion that achieves good results, and compare these results to those of a study of children’s reading accuracy in the primary grades. The comparison highlights areas of weakness in the children’s reading skills, as well as particular phonemes for which the G2P system has difficulty. As part of the process, I also compare and discuss the wide range of discrepancies that exist between various French corpora.