Improving LSTM-CTC based ASR performance in domains with limited training data
Table 9: Experiments with Stochastic dropout combination.
['System', '%WER (Stochastic)', '%WER (Naïve)']
Given our limited compute resources, we were unable to systematically explore the many permutations of dropout combination in a reasonable time frame. We find that while not all stochastic dropout combination results show better performance over naïve dropout combination, in the case of sequence based NML/Forward dropout combination we see an additional 6.6% relative reduction in WER over naïve dropout combination.