Fast and Accurate Recurrent Neural Network Acoustic Models for Speech Recognition
Table 1: WERs for conventional and CTC initialization of LSTM RNN acoustic models.
['Labels', 'CE (%) Uni', 'CE (%) Bi', 'CTC (%) Uni', 'CTC (%) Bi']
As can be expected from trying to learn with 3 state HMM labels, CTC CD state models do not perform well. The unidirectional CE CD phone model is marginally better than the corresponding CE CD state model. CTC CI phone models perform very similarly to CE CD state models. CTC CD phone models give significant improvements over CTC CI phone models – about 8% for unidirectional and 3.5% for bidirectional. Bidirectional models improve over unidirectional ones about 10% for CD state and CI phone models – while improving CTC CD phone models only 5%.