| Crowd++: Unsupervised Speaker Count with Smartphones C Xu, S Li, G Liu, Y Zhang, E Miluzzo, YF Chen, J Li, B Firner The 2013 ACM International Joint Conference on Pervasive and Ubiquitous …, 2013 | 175 | 2013 |
| Advanced LSTM: A Study about Better Time Dependency Modeling in Emotion Recognition F Tao, G Liu | 118 | 2017 |
| I4U submission to NIST SRE 2012: A large-scale collaborative effort for noise-robust speaker verification R Saeidi, KA Lee, T Kinnunen, T Hasan, B Fauve, PM Bousquet, E Khoury, ... Interspeech 2013, 2013 | 95 | 2013 |
| CRSS Systems for 2012 NIST Speaker Recognition Evaluation T Hasan, SO Sadjadi, G Liu, N Shokouhi, H Boril, JHL Hansen Proc. IEEE ICASSP, Vancouver, Canada, 2013 | 91 | 2013 |
| Microsoft speaker diarization system for the voxceleb speaker recognition challenge 2020 X Xiao, N Kanda, Z Chen, T Zhou, T Yoshioka, S Chen, Y Zhao, G Liu, ... ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 84 | 2021 |
| UNCERTAINTY PROPAGATION IN FRONT END FACTOR ANALYSIS FOR NOISE ROBUST SPEAKER RECOGNITION C Yu, G Liu, S Hahm, JHL Hansen ICASSP, 2014 | 58 | 2014 |
| An Investigation into Back-end Advancements for Speaker Recognition in Multi-Session and Noisy Enrollment Scenarios G Liu, JHL Hansen Audio, Speech, and Language Processing, IEEE/ACM Transactions on, 2014 | 53 | 2014 |
| A systematic strategy for robust automatic dialect identification G Liu, JHL Hansen EUSIPCO2011, 2138-2141, 2011 | 48 | 2011 |
| An investigation on back-end for speaker recognition in multi-session enrollment G Liu, T Hasan, H Boril, JH Hansen Proc. IEEE ICASSP, Vancouver, Canada, 2013 | 46 | 2013 |
| Why does self-supervised learning for speech recognition benefit speaker recognition? S Chen, Y Wu, C Wang, S Liu, Z Chen, P Wang, G Liu, J Li, J Wu, X Yu, ... arXiv preprint arXiv:2204.12765, 2022 | 45 | 2022 |
| AN ENSEMBLE FRAMEWORK OF VOICE-BASED EMOTION RECOGNITION SYSTEM FOR FILMS AND TV PROGRAMS F Tao, G Liu, Q Zhao ICASSP2018, 2018 | 40 | 2018 |
| Unsupervised accent classification for deep data fusion of accent and language information JHL Hansen, G Liu Speech Communication 78, 19-33, 2016 | 39 | 2016 |
| Joint information from Nonlinear and linear features for spoofing detection: an i-vector/DNN based approach C Zhang, S Ranjan, MK Nandwana, Q Zhang, A Misra, G Liu, F Kelly, ... ICASSP, 2016 | 34 | 2016 |
| Robust feature front-end for speaker identification G Liu, Y Lei, JHL Hansen Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International …, 2012 | 33 | 2012 |
| Dialect identification: Impact of differences between read versus spontaneous speech G Liu, Y Lei, JHL Hansen 2010 18th European Signal Processing Conference, 2003-2006, 2010 | 31 | 2010 |
| A novel feature extraction strategy for multi-stream robust emotion identification. G Liu, Y Lei, JHL Hansen Interspeech, 482-485, 2010 | 27 | 2010 |
| Autoencoder-based Semi-Supervised Curriculum Learning For Out-of-domain Speaker Verification S Zheng, G Liu, H Suo, Y Lei Proc. Interspeech, 4360-4364, 2019 | 26 | 2019 |
| The I4U Mega Fusion and Collaboration for NIST Speaker Recognition Evaluation 2016 KA Lee, V Hautamaki, T Kinnunen, A Larcher, C Zhang, A Nautsch, ... Interspeech2017, 2017 | 26 | 2017 |
| i-Vector Based Physical Task Stress Detection with Different Fusion Strategies C Zhang, G Liu, C Yu, JHL Hansen Interspeech, 2015 | 23 | 2015 |
| Exploring Hilbert envelope based acoustic features in i-vector speaker verification using HT-PLDA JW Suh, SO Sadjadi, G Liu, T Hasan, KW Godin, JHL Hansen | 23 | 2011 |
John HansenAssociate Dean for Research; Erik Jonsson School of Engineering, University of Texas at DallasVerified email at utdallas.edu
