String Transduction with Target Language Models and Insertion Handling
Table 7: Word-level accuracy (in %) on phoneme-to-grapheme conversion with large training sets.
['[EMPTY]', 'NetTalk', 'Brulex', 'CMU']
The P2G results obtained by Sequitur in our experiments are slightly lower than those reported in the original paper, which is attributable to differences in data splits, tuned hyper-parameters, and/or the presence of stress markers in the data. Sequitur still outperforms the baseline DTL, but DTLM substantially outperforms both Sequitur and the RNN on both the NetTalk and Brulex datasets, with smaller gains on the much larger CMUDict. We conclude that our results advance the state of the art on phoneme-to-grapheme conversion.