Phoneme-grapheme based speech recognition system

State-of-the-art ASR systems typically use phonemes as the subword units. We investigate a system where the word models are defined in-terms of two different subword units, i.e., phonemes and graphemes. We train models for both the subword units, and then perform decoding using either both or just one subword unit. We have studied this system for American English where there is weak correspondence between grapheme and phoneme. We carried out the study in the framework of a state-of-the-art hybrid HMM/ANN system. The results show that there is good potential in using graphemes as auxiliary subword units.