An investigation of deep neural networks for noise robust speech recognition ML Seltzer, D Yu, Y Wang 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 637 | 2013 |
Towards end-to-end spoken language understanding D Serdyuk, Y Wang, C Fuegen, A Kumar, B Liu, Y Bengio 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 111 | 2018 |
Efficient lattice rescoring using recurrent neural network language models X Liu, Y Wang, X Chen, MJF Gales, PC Woodland 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 86 | 2014 |
Adaptation of deep neural network acoustic models using factorised i-vectors P Karanasou, Y Wang, MJF Gales, PC Woodland Fifteenth Annual Conference of the International Speech Communication …, 2014 | 78 | 2014 |
Efficient GPU-based training of recurrent neural network language models using spliced sentence bunch X Chen, Y Wang, X Liu, MJF Gales, PC Woodland Fifteenth Annual Conference of the International Speech Communication …, 2014 | 70 | 2014 |
Simplifying long short-term memory acoustic models for fast training and decoding Y Miao, J Li, Y Wang, SX Zhang, Y Gong 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 67 | 2016 |
Transformer-based acoustic modeling for hybrid speech recognition Y Wang, A Mohamed, D Le, C Liu, A Xiao, J Mahadeokar, H Huang, ... ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 65 | 2020 |
Speaker and noise factorization for robust speech recognition Y Wang, MJF Gales IEEE Transactions on Audio, Speech, and Language Processing 20 (7), 2149-2158, 2012 | 56 | 2012 |
Transformer-transducer: End-to-end speech recognition with self-attention CF Yeh, J Mahadeokar, K Kalgaonkar, Y Wang, D Le, M Jain, K Schubert, ... arXiv preprint arXiv:1910.12977, 2019 | 41 | 2019 |
Investigations on speaker adaptation of LSTM RNN models for speech recognition C Liu, Y Wang, K Kumar, Y Gong 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 40 | 2016 |
Small-footprint high-performance deep neural network-based speech recognition using split-VQ Y Wang, J Li, Y Gong 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 37 | 2015 |
Speaker and noise factorisation on the AURORA4 task YQ Wang, MJF Gales Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International …, 2011 | 29 | 2011 |
Model-based approaches to handling additive noise in reverberant environments MJF Gales, YQ Wang Hands-free Speech Communication and Microphone Arrays (HSCMA), 2011 Joint …, 2011 | 27 | 2011 |
Sample-separation-margin based minimum classification error training of pattern classifiers with quadratic discriminant functions Y Wang, Q Huo Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International …, 2010 | 20 | 2010 |
Semi-Supervised Training in Deep Learning Acoustic Model. Y Huang, Y Wang, Y Gong Interspeech, 3848-3852, 2016 | 19 | 2016 |
End-to-end contextual speech recognition using class language models and a token passing decoder Z Chen, M Jain, Y Wang, ML Seltzer, C Fuegen ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 18 | 2019 |
A study of designing compact recognizers of handwritten Chinese characters using multiple-prototype based classifiers Y Wang, Q Huo 2010 International Conference on Pattern Recognition, 1872-1875, 2010 | 17 | 2010 |
Building compact recognizers of handwritten Chinese characters using precision constrained Gaussian model, minimum classification error training and parameter compression Y Wang, Q Huo International journal on document analysis and recognition 14 (3), 255-262, 2011 | 15 | 2011 |
Streaming Transformer-based Acoustic Models Using Self-attention with Augmented Memory C Wu, Y Wang, Y Shi, CF Yeh, F Zhang arXiv preprint arXiv:2005.08042, 2020 | 13 | 2020 |
Tandem system adaptation using multiple linear feature transforms YQ Wang, MJF Gales 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 13 | 2013 |