| Self-attentive speaker embeddings for text-independent speaker verification. Y Zhu, T Ko, D Snyder, B Mak, D Povey Interspeech 2018, 2-6, 2018 | 310 | 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 | 184 | 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 | 167 | 1996 |
| Subspace distribution clustering hidden Markov model E Bocchieri, BKW Mak IEEE transactions on Speech and Audio Processing 9 (3), 264-275, 2001 | 149 | 2001 |
| A study of endpoint detection algorithms in adverse conditions: incidence on a DTW and HMM recognizer JC Junqua, B Reaves, B Mak Proc. Eurospeech 1991, 1371-1374, 1991 | 146 | 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 | 139 | 2015 |
| 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 | 132 | 2020 |
| 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 | 128 | 2022 |
| 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 | 107 | 2003 |
| C2slr: Consistency-enhanced continuous sign language recognition R Zuo, B Mak Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 104 | 2022 |
| 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 | 91 | 2014 |
| 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 |
| 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 | 70 | 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 |
| Natural language-assisted sign language recognition R Zuo, F Wei, B Mak Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 57 | 2023 |
| 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 | 49 | 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 |
| A comparative study of acoustic and linguistic features classification for alzheimer's disease detection J Li, J Yu, Z Ye, S Wong, M Mak, B Mak, X Liu, H Meng ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 42 | 2021 |
| Subspace distribution clustering for continuous observation density hidden Markov models. E Bocchieri, B Mak Eurospeech, 107-110, 1997 | 42 | 1997 |
Tom KoByteDance AI Lab Hong KongOverená e-mailová adresa na: bytedance.com
