| The Kaldi speech recognition toolkit D Povey, A Ghoshal, G Boulianne, L Burget, O Glembek, N Goel, ... IEEE 2011 workshop on automatic speech recognition and understanding, 2011 | 4963 | 2011 |
| Very deep convolutional neural networks for noise robust speech recognition Y Qian, M Bi, T Tan, K Yu IEEE/ACM Transactions on Audio, Speech, and Language Processing 24 (12 …, 2016 | 231 | 2016 |
| Deep feature for text-dependent speaker verification Y Liu, Y Qian, N Chen, T Fu, Y Zhang, K Yu Speech Communication 73, 1-13, 2015 | 159 | 2015 |
| Generating exact lattices in the WFST framework D Povey, M Hannemann, G Boulianne, L Burget, A Ghoshal, M Janda, ... 2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012 | 147 | 2012 |
| Reshaping deep neural network for fast decoding by node-pruning T He, Y Fan, Y Qian, T Tan, K Yu 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 107 | 2014 |
| CUED-RNNLM—An open-source toolkit for efficient training and evaluation of recurrent neural network language models X Chen, X Liu, Y Qian, MJF Gales, PC Woodland 2016 IEEE international conference on acoustics, speech and signal …, 2016 | 86 | 2016 |
| Multi-task learning for text-dependent speaker verification N Chen, Y Qian, K Yu Sixteenth annual conference of the international speech communication …, 2015 | 82 | 2015 |
| Cluster adaptive training for deep neural network T Tan, Y Qian, M Yin, Y Zhuang, K Yu 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 71 | 2015 |
| Robust deep feature for spoofing detection—The SJTU system for ASVspoof 2015 challenge N Chen, Y Qian, H Dinkel, B Chen, K Yu Sixteenth Annual Conference of the International Speech Communication …, 2015 | 66 | 2015 |
| Overview of BTAS 2016 speaker anti-spoofing competition P Korshunov, S Marcel, H Muckenhirn, AR Gonçalves, AGS Mello, ... 2016 IEEE 8th international conference on biometrics theory, applications …, 2016 | 64 | 2016 |
| Very deep convolutional neural networks for robust speech recognition Y Qian, PC Woodland 2016 IEEE Spoken Language Technology Workshop (SLT), 481-488, 2016 | 61 | 2016 |
| Deep extractor network for target speaker recovery from single channel speech mixtures J Wang, J Chen, D Su, L Chen, M Yu, Y Qian, D Yu arXiv preprint arXiv:1807.08974, 2018 | 60 | 2018 |
| Recognizing multi-talker speech with permutation invariant training D Yu, X Chang, Y Qian arXiv preprint arXiv:1704.01985, 2017 | 57 | 2017 |
| Deep features for automatic spoofing detection Y Qian, N Chen, K Yu Speech Communication 85, 43-52, 2016 | 49 | 2016 |
| Single-channel multi-talker speech recognition with permutation invariant training Y Qian, X Chang, D Yu Speech Communication 104, 1-11, 2018 | 47 | 2018 |
| Adaptive very deep convolutional residual network for noise robust speech recognition T Tan, Y Qian, H Hu, Y Zhou, W Ding, K Yu IEEE/ACM Transactions on Audio, Speech, and Language Processing 26 (8), 1393 …, 2018 | 46 | 2018 |
| Very deep convolutional neural networks for LVCSR M Bi, Y Qian, K Yu Sixteenth Annual Conference of the International Speech Communication …, 2015 | 46 | 2015 |
| End-to-end spoofing detection with raw waveform CLDNNS H Dinkel, N Chen, Y Qian, K Yu 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 45 | 2017 |
| Speaker-aware training of LSTM-RNNs for acoustic modelling T Tan, Y Qian, D Yu, S Kundu, L Lu, KC Sim, X Xiao, Y Zhang 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 45 | 2016 |
| What does the speaker embedding encode? S Wang, Y Qian, K Yu Interspeech, 1497-1501, 2017 | 38 | 2017 |
