Yanmin Qian
Yanmin Qian
Associate Professor, Shanghai Jiao Tong University
Verified email at - Homepage
Cited by
Cited by
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
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
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
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
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
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
Multi-task learning for text-dependent speaker verification
N Chen, Y Qian, K Yu
Sixteenth annual conference of the international speech communication …, 2015
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
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
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
Recognizing multi-talker speech with permutation invariant training
D Yu, X Chang, Y Qian
arXiv preprint arXiv:1704.01985, 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
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
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
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
Very deep convolutional neural networks for robust speech recognition
Y Qian, PC Woodland
2016 IEEE Spoken Language Technology Workshop (SLT), 481-488, 2016
Single-channel multi-talker speech recognition with permutation invariant training
Y Qian, X Chang, D Yu
Speech Communication 104, 1-11, 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
End-to-end monaural multi-speaker ASR system without pretraining
X Chang, Y Qian, K Yu, S Watanabe
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
Deep features for automatic spoofing detection
Y Qian, N Chen, K Yu
Speech Communication 85, 43-52, 2016
The system can't perform the operation now. Try again later.
Articles 1–20