暂无分享,去创建一个
Zhiheng Huang | Songbai Pu | Yisen Wang | Xuejiao Deng | Zhiheng Huang | Yisen Wang | Xuejiao Deng | Songbai Pu
[1] Yajie Miao,et al. EESEN: End-to-end speech recognition using deep RNN models and WFST-based decoding , 2015, 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU).
[2] Nikos Komodakis,et al. Wide Residual Networks , 2016, BMVC.
[3] Dimitri Palaz,et al. Analysis of CNN-based speech recognition system using raw speech as input , 2015, INTERSPEECH.
[4] Yu Zhang,et al. Very deep convolutional networks for end-to-end speech recognition , 2016, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[5] Daniel Povey,et al. The Kaldi Speech Recognition Toolkit , 2011 .
[6] Gerald Penn,et al. Convolutional Neural Networks for Speech Recognition , 2014, IEEE/ACM Transactions on Audio, Speech, and Language Processing.
[7] Lukás Burget,et al. Recurrent neural network based language model , 2010, INTERSPEECH.
[8] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[9] Philip C. Woodland,et al. Very deep convolutional neural networks for robust speech recognition , 2016, 2016 IEEE Spoken Language Technology Workshop (SLT).
[10] Dong Yu,et al. Automatic Speech Recognition: A Deep Learning Approach , 2014 .
[11] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[12] Chong Wang,et al. Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin , 2015, ICML.
[13] Jonathan G. Fiscus,et al. A post-processing system to yield reduced word error rates: Recognizer Output Voting Error Reduction (ROVER) , 1997, 1997 IEEE Workshop on Automatic Speech Recognition and Understanding Proceedings.
[14] Jiaqi Liu,et al. Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognition , 2016 .
[15] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Tara N. Sainath,et al. Learning the speech front-end with raw waveform CLDNNs , 2015, INTERSPEECH.
[17] Erich Elsen,et al. Deep Speech: Scaling up end-to-end speech recognition , 2014, ArXiv.
[18] Haihua Xu,et al. Minimum Bayes Risk decoding and system combination based on a recursion for edit distance , 2011, Comput. Speech Lang..
[19] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[20] Jungwon Lee,et al. Residual LSTM: Design of a Deep Recurrent Architecture for Distant Speech Recognition , 2017, INTERSPEECH.
[21] Geoffrey Zweig,et al. Deep Convolutional Neural Networks with Layer-Wise Context Expansion and Attention , 2016, INTERSPEECH.
[22] Yoshua Bengio,et al. Convolutional networks for images, speech, and time series , 1998 .
[23] Jürgen Schmidhuber,et al. Framewise phoneme classification with bidirectional LSTM and other neural network architectures , 2005, Neural Networks.
[24] Jürgen Schmidhuber,et al. Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks , 2006, ICML.
[25] Vaibhava Goel,et al. Advances in Very Deep Convolutional Neural Networks for LVCSR , 2016, INTERSPEECH.
[26] Andrew W. Senior,et al. Long short-term memory recurrent neural network architectures for large scale acoustic modeling , 2014, INTERSPEECH.
[27] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.