Acknowledgements
Table 6.4: Performance of the proposed network of DNN achieved at various levels of the architecture.
['Dataset', 'Level 0', 'Level 1', 'Level 2']
One can note that the performance become progressively better as the level of the network of DNNs increases till level 2. As expected, the first level speech recognizer (SR DNN-0) performs similarly to the single DNN baseline. The second level (SR DNN-1) is based on a simple cascade between a speech enhancement and a speech recognition DNNs, and thus provides results similar to that obtained with standard joint training. The third level (SR DNN-2) achieves the best performance, confirming that the progressive interaction of the DNNs involved in the DSR process helps in improving the system performance. No additional benefits have been observed for the considered tasks by adding more than 3 levels. The number of communication levels, however, can be regarded as an hyperparameter of the architecture and its best value might be task-dependent. In general, one should anyway expect a diminishing return when increasing N.