| 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 | 7290 | 2011 |
| Wavlm: Large-scale self-supervised pre-training for full stack speech processing S Chen, C Wang, Z Chen, Y Wu, S Liu, Z Chen, J Li, N Kanda, T Yoshioka, ... IEEE Journal of Selected Topics in Signal Processing 16 (6), 1505-1518, 2022 | 1000 | 2022 |
| 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 | 379 | 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 | 209 | 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 | 183 | 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 | 161 | 2014 |
| Margin matters: Towards more discriminative deep neural network embeddings for speaker recognition X Xiang, S Wang, H Huang, Y Qian, K Yu 2019 Asia-Pacific Signal and Information Processing Association Annual …, 2019 | 136 | 2019 |
| Multi-task learning for text-dependent speaker verification N Chen, Y Qian, K Yu Sixteenth annual conference of the international speech communication …, 2015 | 120 | 2015 |
| MIMO-Speech: End-to-end multi-channel multi-speaker speech recognition X Chang, W Zhang, Y Qian, J Le Roux, S Watanabe 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU …, 2019 | 114 | 2019 |
| 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 | 103 | 2018 |
| 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 | 101 | 2016 |
| 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 | 101 | 2015 |
| End-to-end multi-speaker speech recognition with transformer X Chang, W Zhang, Y Qian, J Le Roux, S Watanabe ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 100 | 2020 |
| Recognizing multi-talker speech with permutation invariant training D Yu, X Chang, Y Qian arXiv preprint arXiv:1704.01985, 2017 | 100 | 2017 |
| 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 | 100 | 2016 |
| Large-scale self-supervised speech representation learning for automatic speaker verification Z Chen, S Chen, Y Wu, Y Qian, C Wang, S Liu, Y Qian, M Zeng ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 94 | 2022 |
| Past review, current progress, and challenges ahead on the cocktail party problem Y Qian, C Weng, X Chang, S Wang, D Yu Frontiers of Information Technology & Electronic Engineering 19, 40-63, 2018 | 90 | 2018 |
| 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 | 84 | 2017 |
| Single-channel multi-talker speech recognition with permutation invariant training Y Qian, X Chang, D Yu Speech Communication 104, 1-11, 2018 | 82 | 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 | 82 | 2018 |
