Fine context, low-rank, softplus deep neural networks for mobile speech recognition

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2014, Pages 7644-7648

  Senior, Andrew ^a   Lei, Xin ^a  

^a GOOGLE INC   (United States)

Author keywords

Deep neural networks; embedded recognizer; hybrid neural network speech recognition; low rank approximation; mobile speech recognition; singular value decomposition; softplus nonlinearity; Voice Search

Indexed keywords

SIGNAL PROCESSING; SINGULAR VALUE DECOMPOSITION;

DEEP NEURAL NETWORKS; EMBEDDED RECOGNIZER; HYBRID NEURAL NETWORKS; LOW RANK APPROXIMATIONS; SOFTPLUS NONLINEARITY; VOICE SEARCHES;

SPEECH RECOGNITION;

EID: 84905284804     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2014.6855087     Document Type: Conference Paper

References (11)

1. X. Lei, A. Senior, A. Gruenstein, and J. Sorenson, "Accurate and compact large vocabulary speech recognition on mobile devices, " in Proc. Interspeech, 2013.
2. H. Liao, E. McDermott, and A. Senior, "Large scale deep neural network acoustic modeling with semi-supervised training data for YouTube video transcription, " in Proc. ASRU, 2013.
3. M. D. Zeiler, M. Ranzato, R. Monga, M. Mao, K. Yang, Q. V. Le, P. Nguyen, A. Senior, V. Vanhoucke, J. Dean, and G. E. Hinton, "On rectified linear units for speech processing, " in ICASSP, 2013.
4. T. N. Sainath, B. Kingsbury, V. Sindhwani, E. Arisoy, and B. Ramabhadran, "Low-rank matrix factorization for deep neural network training with high-dimensional output targets, " in Proc. ICASSP, 2013.
5. A. Senior, G. Heigold, M. Ranzato, and K. Yang, "An empirical study of learning rates in deep neural networks for speech recognition, " in Proc. ICASSP, 2013.
6. V. Vanhoucke, A. Senior, and M. Z. Mao, "Improving the speed of neural networks on CPUs, " in Proc. Deep Learning and Unsupervised Feature Learning NIPS Workshop, 2011.
7. J. Xue, J. Li, and Y. Gong, "Restructuring of deep neural network acoustic models with singular value decomposition, " in Proc. Interspeech, 2013.
8. X. Glorot, A. Bordes, and Y. Bengio, "Deep sparse rectifier neural networks, " in Proc. AISTATS, 2011.
9. A. Maas, A. Jannun, and A. Ng, "Rectifier nonlinearities improve neural network acoustic models, " in ICML Workshop on Deep Learning for Audio, Speech and Language Processing, 2013.
10. D. Yu, F. Seide, G. Li, and L. Deng, "Exploiting sparseness in deep neural networks for large vocabulary speech recognition, " in ICASSP, 2012.
11. P. Golik, P. Doetsch, and H. Ney, "Cross-entropy vs. squared error training: a theoretical and experimental comparison, " in Proc. Interspeech, 2013.