Introduction -- Gaussian mixture models -- Hidden Markov models and the variants -- Deep neural networks -- Advanced model initialization techniques -- Deep neural network-hidden Markov model hybrid systems -- Training and decoding speedup -- Deep neural network sequence-discriminative training -- Feature representation learning in deep neural networks -- Fuse deep neural network and gaussian mixture model systems -- Adaptation of deep neural networks -- Representation sharing and transfer in deep neural networks -- Recurrent neural networks and related models -- Computational network -- Summary and future directions