Improving LSTM-CTC based ASR performance in domains with limited training data
Table 4: Experiments with frame stacking and striding.
['System', '%WER ( [ITALIC] dev-clean)']
We conducted several experiments with stacking and striding, and observed a consistent drop in performance. We find that 9-fold max perturbation data augmentation provides a slight, but relatively stronger, performance improvement (10.1% vs. 9.1% relative) when compared to the model based on the base features.