End-to-end attention-based large vocabulary speech recognition
Table 1: Character Error Rate (CER) and Word Error Rate (WER) scores for our setup on the Wall Street Journal Corpus in comparison with other results from the literature. Note that our results are not directly comparable with those of networks predicting phonemes instead of characters, since phonemes are easier targets.
['Model', 'CER', 'WER']
Our model shows performance superior to that of CTC systems when no external language model is used. The improvement from adding an external language model is however much larger for CTC-based systems. (11.3% vs 9.0%) when the same language models are used.