Improvements to Deep Convolutional Neural Networks for LVCSR
Table 12: WER on Broadcast News, 50 hours
['model', 'dev04f', 'rt04']
The proposed CNN hybrid system offers between a 6-7% relative improvement over the DNN hybrid, and a 2-3% relative improvement over the old CNN hybrid system. While the proposed CNN-based feature system offers a modest 1% improvement over the old CNN-based feature system, this slight improvements with feature-based system is not surprising all. We have observed huge relative improvements in WER (10-12%) on a hybrid sequence trained DNN with 512 output targets, compared to a hybrid CE-trained DNN. Feature-based systems use the neural network to learn a feature transformation, and seem to saturate in performance even when the hybrid system used to extract the features improves. Thus, as the table shows, there is more potential to improve a hybrid system as opposed to a feature-based system.