Joint decoding for phoneme-grapheme continuous speech recognition
Standard ASR systems typically use phonemes as the subword units. Preliminary studies have shown that the performance of ASR systems could be improved by using graphemes as additional subword units. We investigate such a system where the word models are defined in terms of two different subword units, i.e., phoneme and grapheme. During training, models for both the subword units are trained, and then, during recognition, either both or just one subword unit is used. We have studied this system for a continuous speech recognition task in American English. Our studies show that grapheme information used along with phoneme information improves the performance of ASR.