Deep models such as DNN have the potential to be much more representationally efficient for feature learning than shallow models like GMM.
instead of GMM, we use DNN (DBN, DAE and HCDAE) to learn new non-parametric features, which has the similar evolution in speech recognition Hinton et al., 2012).