Spectral feature mapping with mimic loss for robust speech recognition
Table 3: Performance comparison with other studies on the CHiME2 test set.
['Study', 'WER']
the performance of our system relative to other published results in the field. (e.g., PNCC, MRCG). We use an off-the-shelf Kaldi recipe using DNN-HMM to do speech recognition, as well as a simple 2 layer feed-forward network to do spectral mapping. Again, mimic loss can theoretically be used to improve the results of any front-end system.