Fast and Accurate Recurrent Neural Network Acoustic Models for Speech Recognition
Table 2: WERs (%) for sequence-trained LSTM RNN models.
['Labels', 'Initialization Method', 'Initialization Uni', 'Initialization Bi', '+sMBR Uni', '+sMBR Bi']
We can see that sMBR training consistently improves all of the models initially trained with CE or CTC loss about 10% relative. We obtain best results with CTC CD phone models outperforming the second best model about 8% for unidirectional and 4% for bidirectional model.