Deliberation Model Based Two-Pass End-to-End Speech Recognition
Table 2: WERs (%) of baseline RNN-T model and deliberation models with different attention setup.
['ID', 'Model', 'WER (%)']
We are curious about how different attention (cb vs ce) contribute to deliberation, and thus train separate models where we attend to either acoustics (E5) or text (E6) alone in training and inference. By using both attentions (E4), the model gains another 11% relative improvement. It seems surprising that E6 performs equally to E5. We note this could be because E6 has a bidirectional encoder while E5 does not.