Complex Evolution Recurrent Neural Networks (ceRNNs)
Table 2: Performance (WER) improvements observed with 512, 1024 and 2048 ceRNN nodes.
['Model', 'Clean', 'Noisy']
Since the ceRNN model parameters grow only linearly in the size (nodes) of the layer in contrast to standard matrix-based layers (O(7N)vs. O(N2)) , the computational cost also scales linearly. The ceRNN with 2048 nodes (with only 14k additional parameters) appears to provide the most performance gain. Increasing the number of nodes further to 4096 increased the performance only marginally.