Yao X, Li Y H, Shan G R, et al. Research on Tibetan Isolated-word Speech Recognition System. Journal of Northwest University for Nationalities: Natural Science, 2009, 30(1): 29-36,50 (in Chinese) (姚 徐,李永宏,单广荣,等.藏语孤立词语音识别系统研究.西北民族大学学报:自然科学版, 2009, 30(1): 29-36,50)
[2]
Han Q H, Yu H Z. Research on Speech Recognition for Ando Tibetan Based on HMM. Software Guide, 2010, 9(7): 173-175 (in Chinese) (韩清华,于洪志.基于HMM的安多藏语非特定人孤立词语音识别研究. 软件导刊, 2010, 9(7): 173-175)
[3]
Li G Y, Meng M. Research on Acoustic Model of Large-Vocabulary Continuous Speech Recognition for Lhasa Tibetan. Computer Engineering, 2012, 38(5): 189-191(in Chinese) (李冠宇,孟 猛.藏语拉萨话大词表连续语音识别声学模型研究.计算机工程, 2012, 38(5): 189-191)
[4]
Dahl G E, Yu D, Deng L, et al. Context-Dependent Pre-trained Deep Neural Networks for Large Vocabulary Speech Recognition. IEEE Trans on Audio, Speech, and Language Processing, 2012, 20(1): 30-42
[5]
Hinton G E, Osindero S, Teh Y W. A Fast Learning Algorithm for Deep Belief Nets. Neural Computation, 2006, 18(7): 1527-1554
[6]
Beulen K, Ney H. Automatic Question Generation for Decision Tree Based State Tying // Proc of the IEEE International Conference on Acoustics, Speech and Signal Processing. Seattle, USA, 1998, II: 805-805
[7]
Singh R, Raj B, Stern R M. Automatic Clustering and Generation of Contextual Questions for Tied States in Hidden Markov Models // Proc of the IEEE International Conference on Acoustics, Speech and Signal Processing. Phoenix, USA, 1999, I: 117-120
[8]
Huang J T, Li J Y, Yu D, et al. Cross-Language Knowledge Transfer Using Multilingual Deep Neural Network with Shared Hidden Layers // Proc of the IEEE International Conference on Acoustics, Speech and Signal Processing. Vancouver, Canada, 2013: 7304-7308
[9]
Carreira-Perpinan M A, Hinton G E. On Contrastive Divergence Learning. [EB/OL]. [2013-02-15]. www.docin.com/p-33657so63.html
[10]
Mohamed A, Dahl G E, Hinton G. Acoustic Modeling Using Deep Belief Networks. IEEE Trans on Audio, Speech, and Language Processing, 2012, 20(1): 14-22
[11]
Erhan D, Bengio Y, Courville A, et al. Why Does Unsupervised Pre-training Help Deep Learning? Journal of Machine Learning Research. 2010, 11: 625-660
[12]
Deng L, Seltzer M, Yu D, et al. Binary Coding of Speech Spectrograms Using a Deep Auto-Encoder // Proc of the 11th Annual Conference of the International Speech Communication Association. Makuhari, Japan, 2010: 1692-1695
