Self-attentive speaker embeddings for text-independent speaker verification. Y Zhu, T Ko, D Snyder, B Mak, D Povey Interspeech 2018, 3573-3577, 2018 | 298 | 2018 |
A robust algorithm for word boundary detection in the presence of noise JC Junqua, B Mak, B Reaves IEEE Transactions on speech and audio processing 2 (3), 406-412, 1994 | 297 | 1994 |
Phone clustering using the Bhattacharyya distance B Mak, E Barnard Proceeding of Fourth International Conference on Spoken Language Processing …, 1996 | 181 | 1996 |
The contribution of consonants versus vowels to word recognition in fluent speech RA Cole, Y Yan, B Mak, M Fanty, T Bailey 1996 IEEE International Conference on Acoustics, Speech, and Signal …, 1996 | 164 | 1996 |
Subspace distribution clustering hidden Markov model E Bocchieri, BKW Mak IEEE transactions on Speech and Audio Processing 9 (3), 264-275, 2001 | 147 | 2001 |
A study of endpoint detection algorithms in adverse conditions: incidence on a DTW and HMM recognizer JC Junqua, B Reaves, B Mak 2nd European Conference on Speech Communication and Technology (Eurospeech 1991), 1991 | 147 | 1991 |
Multitask learning of deep neural networks for low-resource speech recognition D Chen, BKW Mak IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (7), 1172 …, 2015 | 129 | 2015 |
PLASER: Pronunciation learning via automatic speech recognition B Mak, M Siu, M Ng, YC Tam, YC Chan, KW Chan, KY Leung, S Ho, ... Proceedings of the HLT-NAACL 03 workshop on Building educational …, 2003 | 106 | 2003 |
Stochastic fine-grained labeling of multi-state sign glosses for continuous sign language recognition Z Niu, B Mak Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 103 | 2020 |
Joint acoustic modeling of triphones and trigraphemes by multi-task learning deep neural networks for low-resource speech recognition D Chen, B Mak, CC Leung, S Sivadas 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 83 | 2014 |
Two-stream network for sign language recognition and translation Y Chen, R Zuo, F Wei, Y Wu, S Liu, B Mak Advances in Neural Information Processing Systems 35, 17043-17056, 2022 | 82 | 2022 |
Tone recognition of isolated Cantonese syllables T Lee, PC Ching, LW Chan, YH Cheng, B Mak IEEE Transactions on speech and audio processing 3 (3), 204-209, 1995 | 81 | 1995 |
C2slr: Consistency-enhanced continuous sign language recognition R Zuo, B Mak Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 67 | 2022 |
End-to-end low-resource lip-reading with maxout CNN and LSTM I Fung, B Mak 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 66 | 2018 |
Kernel eigenvoice speaker adaptation B Mak, JT Kwok, S Ho IEEE Transactions on Speech and Audio Processing 13 (5), 984-992, 2005 | 62 | 2005 |
A comparison of various adaptation methods for speaker verification with limited enrollment data MW Mak, R Hsiao, B Mak 2006 IEEE international conference on acoustics speech and signal processing …, 2006 | 50 | 2006 |
Improving reference speaker weighting adaptation by the use of maximum-likelihood reference speakers B Mak, TC Lai, R Hsiao 2006 IEEE International Conference on Acoustics Speech and Signal Processing …, 2006 | 43 | 2006 |
Subspace distribution clustering for continuous observation density hidden Markov models. E Bocchieri, B Mak Eurospeech, 107-110, 1997 | 43 | 1997 |
Kernel eigenspace-based MLLR adaptation BKW Mak, RWH Hsiao IEEE transactions on audio, speech, and language processing 15 (3), 784-795, 2007 | 40 | 2007 |
Natural language-assisted sign language recognition R Zuo, F Wei, B Mak Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 34 | 2023 |