Complex Evolution Recurrent Neural Networks (ceRNNs)
Table 1: Performance (WER) comparison of the LSTM, the uRNN+LSTM, and the ceRNN+LSTM models.
['Model', 'Clean', 'Noisy']
Attempts to train a simple RNN as a test layer with different learning rate failed. The unitary RNN layer hurts the ASR performance when compared to the baseline system. On the other hand, the ceRNN gives a marginal and consistent gain over the baseline system. To rule out the possibility that the ceRNN is only renormalizing the data, we introduced a normalization layer before uRNN. That still does not help improve the performance of the uRNN models.