Investigations on Phoneme-Based End-To-End Speech Recognition
Table 5: On Switchboard 300h, comparing results from the literature. One big difference in varying results is the different amount of training time, which we state as number of epochs. ∗with word-disambiguate symbols.
['Work', 'Label Unit', 'Label Type', 'Label #', '#Ep', 'LM', 'WER[%] Hub500', 'WER[%] Hub500', 'WER[%] Hub500', 'WER[%] Hub501', 'WER[%] RT03']
We observe that many other works train for much longer, and that seems to lead to yet better results. Our final phoneme-based models perform slightly better than our final grapheme-based models, although they are very close.