Unpaired Speech Enhancement by Acoustic and Adversarial Supervision for Speech Recognition
TABLE III: WERs (%) of obtained using different training data of CHiME-4
['Method', 'Training Data', 'Test WER (%) simulated', 'Test WER (%) real']
Table III shows the WERs on the simulated and real test sets when AAS is trained with different training data. With the simulated dataset as the training data, FSEGAN (29.6%) does not generalize well compared to AAS (25.2%) in terms of WER. With the real dataset as the training data, AAS shows severe overfitting since the size of training data is small. When AAS is trained with simulated and real datasets, it achieves the best result (24.7%) on the real test set.