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2020 – today
- 2025
[i10]Jinchao Li, Yuejiao Wang, Junan Li, Jiawen Kang, Bo Zheng, Simon Wong, Brian Mak, Helene H. Fung, Jean Woo, Man-Wai Mak, Timothy C. Y. Kwok, Vincent C. T. Mok, Xianmin Gong, Xixin Wu, Xunying Liu, Patrick C. M. Wong, Helen Meng:
Detecting Neurocognitive Disorders through Analyses of Topic Evolution and Cross-modal Consistency in Visual-Stimulated Narratives. CoRR abs/2501.03727 (2025)- 2024
- [j22]Ronglai Zuo
, Brian Mak:
Improving Continuous Sign Language Recognition with Consistency Constraints and Signer Removal. ACM Trans. Multim. Comput. Commun. Appl. 20(6): 163:1-163:25 (2024) - [c98]Zhe Niu, Ronglai Zuo, Brian Mak, Fangyun Wei:
A Hong Kong Sign Language Corpus Collected from Sign-interpreted TV News. LREC/COLING 2024: 636-646 - [c97]Ronglai Zuo, Fangyun Wei, Zenggui Chen, Brian Mak, Jiaolong Yang, Xin Tong:
A Simple Baseline for Spoken Language to Sign Language Translation with 3D Avatars. ECCV (49) 2024: 36-54 - [c96]Ronglai Zuo, Fangyun Wei, Brian Mak:
Towards Online Continuous Sign Language Recognition and Translation. EMNLP 2024: 11050-11067 - [i9]Ronglai Zuo, Fangyun Wei, Zenggui Chen, Brian Mak, Jiaolong Yang, Xin Tong:
A Simple Baseline for Spoken Language to Sign Language Translation with 3D Avatars. CoRR abs/2401.04730 (2024) - [i8]Ronglai Zuo, Fangyun Wei, Brian Mak:
Towards Online Sign Language Recognition and Translation. CoRR abs/2401.05336 (2024) - [i7]Zhe Niu, Ronglai Zuo, Brian Mak, Fangyun Wei:
A Hong Kong Sign Language Corpus Collected from Sign-interpreted TV News. CoRR abs/2405.00980 (2024) - 2023
- [j21]Yingke Zhu, Brian Mak:
Bayesian Self-Attentive Speaker Embeddings for Text-Independent Speaker Verification. IEEE ACM Trans. Audio Speech Lang. Process. 31: 1000-1012 (2023) - [c95]Ronglai Zuo, Fangyun Wei, Brian Mak:
Natural Language-Assisted Sign Language Recognition. CVPR 2023: 14890-14900 - [c94]Zhe Niu, Brian Mak:
On the Audio-visual Synchronization for Lip-to-Speech Synthesis. ICCV 2023: 7809-7818 - [c93]Helen Meng, Brian Mak, Man-Wai Mak, Helene H. Fung, Xianmin Gong, Timothy C. Y. Kwok, Xunying Liu, Vincent C. T. Mok, Patrick C. M. Wong, Jean Woo, Xixin Wu, Ka Ho Wong, Sean Shensheng Xu, Naijun Zheng, Ranzo Huang, Jiawen Kang, Xiaoquan Ke, Junan Li, Jinchao Li, Yi Wang:
Integrated and Enhanced Pipeline System to Support Spoken Language Analytics for Screening Neurocognitive Disorders. INTERSPEECH 2023: 1713-1717 - [c92]Ranzo Huang, Brian Mak:
wav2vec 2.0 ASR for Cantonese-Speaking Older Adults in a Clinical Setting. INTERSPEECH 2023: 4958-4962 - [i6]Zhe Niu, Brian Mak:
On the Audio-visual Synchronization for Lip-to-Speech Synthesis. CoRR abs/2303.00502 (2023) - [i5]Ronglai Zuo, Fangyun Wei, Brian Mak:
Natural Language-Assisted Sign Language Recognition. CoRR abs/2303.12080 (2023) - 2022
- [j20]Grant Giesbrecht, Ariel Amsellem, Timo Bauer, Brian Mak, Brian Wynne, Zhihao Qin, Arun Persaud:
Hardware-Control: Instrument control and automation package. J. Open Source Softw. 7(72): 2688 (2022) - [c91]Roshan Mathew, Brian Mak, Wendy Dannels:
Access on Demand: Real-time, Multi-modal Accessibility for the Deaf and Hard-of-Hearing based on Augmented Reality. ASSETS 2022: 2:1-2:6 - [c90]Ronglai Zuo, Brian Mak:
C2SLR: Consistency-enhanced Continuous Sign Language Recognition. CVPR 2022: 5121-5130 - [c89]Raymond Chung, Brian Mak:
Synthesizing Near Native-accented Speech for a Non-native Speaker by Imitating the Pronunciation and Prosody of a Native Speaker. INTERSPEECH 2022: 4302-4306 - [c88]Ronglai Zuo, Brian Mak:
Local Context-aware Self-attention for Continuous Sign Language Recognition. INTERSPEECH 2022: 4810-4814 - [c87]Yutong Chen, Ronglai Zuo, Fangyun Wei, Yu Wu, Shujie Liu, Brian Mak:
Two-Stream Network for Sign Language Recognition and Translation. NeurIPS 2022 - [i4]Yutong Chen, Ronglai Zuo, Fangyun Wei, Yu Wu, Shujie Liu, Brian Mak:
Two-Stream Network for Sign Language Recognition and Translation. CoRR abs/2211.01367 (2022) - [i3]Ronglai Zuo, Brian Mak:
Improving Continuous Sign Language Recognition with Consistency Constraints and Signer Removal. CoRR abs/2212.13023 (2022) - 2021
- [c86]Raymond Chung, Brian Mak:
On-The-Fly Data Augmentation for Text-to-Speech Style Transfer. ASRU 2021: 634-641 - [c85]Xinyuan Yu, Brian Mak:
Non-Parallel Many-To-Many Voice Conversion by Knowledge Transfer from a Text-To-Speech Model. ICASSP 2021: 5924-5928 - [c84]Jinchao Li, Jianwei Yu, Zi Ye, Simon Wong, Man-Wai Mak, Brian Mak, Xunying Liu, Helen Meng:
A Comparative Study of Acoustic and Linguistic Features Classification for Alzheimer's Disease Detection. ICASSP 2021: 6423-6427 - 2020
- [c83]Zhe Niu, Brian Mak:
Stochastic Fine-Grained Labeling of Multi-state Sign Glosses for Continuous Sign Language Recognition. ECCV (16) 2020: 172-186 - [c82]Yingke Zhu, Brian Mak:
Orthogonal Training for Text-Independent Speaker Verification. ICASSP 2020: 6584-6588 - [c81]Zhaoyu Liu, Brian Mak:
Multi-Lingual Multi-Speaker Text-to-Speech Synthesis for Voice Cloning with Online Speaker Enrollment. INTERSPEECH 2020: 2932-2936 - [c80]Yingke Zhu, Brian Mak:
Orthogonality Regularizations for End-to-End Speaker Verification. Odyssey 2020: 17-23 - [i2]Wei Li, Brian Mak:
Transformer based Multilingual document Embedding model. CoRR abs/2008.08567 (2020)
2010 – 2019
- 2019
- [c79]Hengguan Huang, Hao Wang, Brian Mak:
Recurrent Poisson Process Unit for Speech Recognition. AAAI 2019: 6538-6545 - [c78]Yingke Zhu, Tom Ko, Brian Mak:
Mixup Learning Strategies for Text-Independent Speaker Verification. INTERSPEECH 2019: 4345-4349 - 2018
- [j19]Zhili Tan, Man-Wai Mak, Brian Kan-Wing Mak:
DNN-Based Score Calibration With Multitask Learning for Noise Robust Speaker Verification. IEEE ACM Trans. Audio Speech Lang. Process. 26(4): 700-712 (2018) - [j18]Zhili Tan, Man-Wai Mak, Brian Kan-Wing Mak, Yingke Zhu:
Denoised Senone I-Vectors for Robust Speaker Verification. IEEE ACM Trans. Audio Speech Lang. Process. 26(4): 820-830 (2018) - [c77]Ivan Fung, Brian Mak:
End-To-End Low-Resource Lip-Reading with Maxout Cnn and Lstm. ICASSP 2018: 2511-2515 - [c76]Lahiru Samarakoon, Brian Mak, Khe Chai Sim:
learning Effective Factorized Hidden Layer Bases Using Student-Teacher Training for LSTM Acoustic Model Adaptation. ICASSP 2018: 5954-5958 - [c75]Wei Li, Brian Mak:
Fast Derivation of Cross-lingual Document Vectors from Self-attentive Neural Machine Translation Model. INTERSPEECH 2018: 107-111 - [c74]Yingke Zhu, Tom Ko, David Snyder, Brian Mak, Daniel Povey:
Self-Attentive Speaker Embeddings for Text-Independent Speaker Verification. INTERSPEECH 2018: 3573-3577 - [c73]Lahiru Samarakoon, Brian Mak, Albert Y. S. Lam:
Subspace Based Sequence Discriminative Training of LSTM Acoustic Models with Feed-Forward Layers. ISCSLP 2018: 136-140 - [c72]Hengguan Huang, Brian Mak:
WaveNet MH-SRU: Deep and Wide Multiple-history Simple Recurrent Unit for Speech Recognition. ISCSLP 2018: 141-145 - [c71]Ivan Fung, Brian Mak:
Multi-Head Attention for End-to-End Neural Machine Translation. ISCSLP 2018: 250-254 - [c70]Lahiru Samarakoon, Brian Mak, Albert Y. S. Lam:
Domain Adaptation of End-to-end Speech Recognition in Low-Resource Settings. SLT 2018: 382-388 - [i1]Wei Li, Brian Mak:
Fast derivation of neural network based document vectors with distance constraint and negative sampling. CoRR abs/1807.11057 (2018) - 2017
- [c69]Lahiru Samarakoon, Brian Mak:
Unsupervised adaptation of student DNNS learned from teacher RNNS for improved ASR performance. ASRU 2017: 200-205 - [c68]Wei Li, Brian Mak:
Derivation of Document Vectors from Adaptation of LSTM Language Model. EACL (2) 2017: 456-461 - [c67]Lahiru Samarakoon, Khe Chai Sim, Brian Mak:
An investigation into learning effective speaker subspaces for robust unsupervised DNN adaptation. ICASSP 2017: 5035-5039 - [c66]Yingke Zhu, Brian Mak:
Speeding up softmax computations in DNN-based large vocabulary speech recognition by senone weight vector selection. ICASSP 2017: 5335-5339 - [c65]Lahiru Samarakoon, Brian Mak, Khe Chai Sim:
Learning Factorized Transforms for Unsupervised Adaptation of LSTM-RNN Acoustic Models. INTERSPEECH 2017: 744-748 - [c64]Hengguan Huang, Brian Mak:
To Improve the Robustness of LSTM-RNN Acoustic Models Using Higher-Order Feedback from Multiple Histories. INTERSPEECH 2017: 3862-3866 - 2016
- [c63]Zhili Tan, Yingke Zhu, Man-Wai Mak, Brian Kan-Wing Mak:
Senone I-vectors for robust speaker verification. ISCSLP 2016: 1-5 - [c62]Yingke Zhu, Brian Mak:
An investigation of adaptation techniques for building acoustic models for hearing-impaired children in a CAPT application. ISCSLP 2016: 1-5 - 2015
- [j17]Dongpeng Chen, Brian Kan-Wing Mak:
Multitask Learning of Deep Neural Networks for Low-Resource Speech Recognition. IEEE ACM Trans. Audio Speech Lang. Process. 23(7): 1172-1183 (2015) - [c61]Goh Wen Shyan, Brian Mak, Chee-Onn Wong, Tan Yee Lyn, Tey Zi Ming:
The harp of light: a musical string projection mapping. Advances in Computer Entertainment 2015: 43:1-43:3 - [c60]Dongpeng Chen, Brian Mak:
Distinct triphone acoustic modeling using deep neural networks. INTERSPEECH 2015: 2645-2649 - 2014
- [j16]Tom Ko, Brian Kan-Wing Mak:
Eigentrigraphemes for under-resourced languages. Speech Commun. 56: 132-141 (2014) - [c59]Tom Ko, Brian Mak, Cheung-Chi Leung:
Subspace Gaussian mixture model with state-dependent subspace dimensions. ICASSP 2014: 1725-1729 - [c58]Dongpeng Chen, Brian Mak, Cheung-Chi Leung, Sunil Sivadas:
Joint acoustic modeling of triphones and trigraphemes by multi-task learning deep neural networks for low-resource speech recognition. ICASSP 2014: 5592-5596 - [c57]Dongpeng Chen, Brian Mak, Sunil Sivadas:
Joint sequence training of phone and grapheme acoustic model based on multi-task learning deep neural networks. INTERSPEECH 2014: 1083-1087 - [c56]Tom Ko, Brian Kan-Wing Mak, Dongpeng Chen:
Modeling inter-cluster and intra-cluster discrimination among triphones. ISCSLP 2014: 103-107 - 2013
- [j15]Tom Ko, Brian Mak:
Eigentriphones for Context-Dependent Acoustic Modeling. IEEE Trans. Speech Audio Process. 21(6): 1285-1294 (2013) - [c55]Dongpeng Chen, Brian Mak:
Distinct triphone modeling by reference model weighting. ICASSP 2013: 7150-7154 - 2012
- [c54]Brian Mak, Guoli Ye:
Subspace high-density discrete hidden Markov model for automatic speech recognition. EUSIPCO 2012: 1643-1647 - [c53]Tom Ko, Brian Mak:
Derivation of eigentriphones by weighted principal component analysis. ICASSP 2012: 4097-4100 - [c52]Guoli Ye, Dongpeng Chen, Brian Mak:
Transition probabilities are more important than we once thought. ICASSP 2012: 4809-4812 - [c51]Brian Mak, Bin Ma:
Welcome message from the technical program chairs. ISCSLP 2012 - [c50]Guoli Ye, Brian Mak:
Speaker-ensemble hidden Markov modeling for automatic speech recognition. ISCSLP 2012: 6-10 - 2011
- [c49]Tom Ko, Brian Mak:
Eigentriphones: A basis for context-dependent acoustic modeling. ICASSP 2011: 4892-4895 - [c48]Tom Ko, Brian Mak:
A Fully Automated Derivation of State-Based Eigentriphones for Triphone Modeling with No Tied States Using Regularization. INTERSPEECH 2011: 781-784 - 2010
- [c47]Tom Ko, Brian Mak:
Improving speech recognition by explicit modeling of phone deletions. ICASSP 2010: 4858-4861 - [c46]Guoli Ye, Brian Mak:
The use of subvector quantization and discrete densities for fast GMM computation for speaker verification. INTERSPEECH 2010: 1481-1484 - [c45]Guoli Ye, Brian Mak:
Subvector-quantized high-density discrete hidden Markov model and its re-estimation. ISCSLP 2010: 109-113 - [c44]Brian Mak, Tom Ko:
Problems of modeling phone deletion in conversational speech for speech recognition. ISCSLP 2010: 114-118
2000 – 2009
- 2009
- [j14]Brian Kan-Wing Mak, Tsz-Chung Lai, Ivor W. Tsang, James Tin-Yau Kwok:
Maximum Penalized Likelihood Kernel Regression for Fast Adaptation. IEEE Trans. Speech Audio Process. 17(7): 1372-1381 (2009) - [c43]Brian Mak, Tom Ko:
Automatic estimation of decoding parameters using large-margin iterative linear programming. INTERSPEECH 2009: 1219-1222 - [c42]Guoli Ye, Brian Mak, Man-Wai Mak:
Fast GMM computation for speaker verification using scalar quantization and discrete densities. INTERSPEECH 2009: 2327-2330 - 2008
- [c41]Brian Mak, Benny Ng:
Discriminative training by iterative linear programming optimization. ICASSP 2008: 4061-4064 - [c40]Brian Mak, Tom Ko:
Min-max discriminative training of decoding parameters using iterative linear programming. INTERSPEECH 2008: 915-918 - [c39]Chien-Lin Huang, Bin Ma, Chung-Hsien Wu, Brian Mak, Haizhou Li:
Robust speaker verification using short-time frequency with long-time window and fusion of multi-resolutions. INTERSPEECH 2008: 1897-1900 - 2007
- [j13]Brian Kan-Wing Mak, Roger Wend-Huu Hsiao:
Kernel Eigenspace-Based MLLR Adaptation. IEEE Trans. Speech Audio Process. 15(3): 784-795 (2007) - [c38]Kakeung Wong, Man-Hung Siu, Brian Mak:
A model-based estimation of phonotactic language verification performance. INTERSPEECH 2007: 186-189 - [c37]Brian Kan-Wing Mak, Roger Wend-Huu Hsiao:
Robustness of several kernel-based fast adaptation methods on noisy LVCSR. INTERSPEECH 2007: 266-269 - [c36]Xi Yang, Man-Hung Siu, Herbert Gish, Brian Mak:
Boosting with anti-models for automatic language identification. INTERSPEECH 2007: 342-345 - 2006
- [j12]Yiu-Pong Lai, Man-Hung Siu, Brian Mak:
Joint Optimization of the Frequency-Domain and Time-Domain Transformations in Deriving Generalized Static and Dynamic MFCCs. IEEE Signal Process. Lett. 13(11): 707-710 (2006) - [j11]Man-Hung Siu, Brian Mak, Wing-Hei Au:
Minimization of Utterance Verification Error Rate as a Constrained Optimization Problem. IEEE Signal Process. Lett. 13(12): 760-763 (2006) - [j10]Brian Kan-Wing Mak, Roger Wend-Huu Hsiao, Simon Ka-Lung Ho, James T. Kwok:
Embedded kernel eigenvoice speaker adaptation and its implication to reference speaker weighting. IEEE Trans. Speech Audio Process. 14(4): 1267-1280 (2006) - [c35]Brian Mak, Tsz-Chung Lai, Roger Wend-Huu Hsiao:
Improving Reference Speaker Weighting Adaptation by the Use of Maximum-Likelihood Reference Speakers. ICASSP (1) 2006: 229-232 - [c34]Man-Wai Mak, Roger Wend-Huu Hsiao, Brian Mak:
A Comparison of Various Adaptation Methods for Speaker Verification With Limited Enrollment Data. ICASSP (1) 2006: 929-932 - [c33]Ivor W. Tsang, James T. Kwok, Brian Mak, Kai Zhang, Jeffrey Junfeng Pan:
Fast Speaker Adaption Via Maximum Penalized Likelihood Kernel Regression. ICASSP (1) 2006: 997-1000 - [c32]David Rossiter, Gibson Lam, Brian Mak:
Automatic Audio Indexing and Audio Playback Speed Control as Tools for Language Learning. ICWL 2006: 290-299 - [c31]Tsz-Chung Lai, Brian Mak:
Unsupervised Speaker Adaptation Using Reference Speaker Weighting. ISCSLP (Selected Papers) 2006: 380-389 - 2005
- [j9]Brian Mak, James Tin-Yau Kwok, Simon Ka-Lung Ho:
Kernel Eigenvoice Speaker Adaptation. IEEE Trans. Speech Audio Process. 13(5-2): 984-992 (2005) - [j8]Brian Kan-Wing Mak, Kin-Wah Chan:
Pruning Hidden Markov Models With Optimal Brain Surgeon. IEEE Trans. Speech Audio Process. 13(5-2): 993-1003 (2005) - [c30]Brian Mak, Simon Ka-Lung Ho:
Various Reference Speakers Determination Methods for Embedded Kernel Eigenvoice Speaker Adaptation. ICASSP (1) 2005: 981-984 - [c29]Roger Wend-Huu Hsiao, Brian Kan-Wing Mak:
Kernel Eigenspace-based MLLR Adaptation Using Multiple Regression Classes. ICASSP (1) 2005: 985-988 - [c28]Roger Wend-Huu Hsiao, Brian Kan-Wing Mak:
A comparative study of two kernel eigenspace-based speaker adaptation methods on large vocabulary continuous speech recognition. INTERSPEECH 2005: 1797-1800 - [c27]Brian Mak, Jeff Siu-Kei Au-Yeung, Yiu-Pong Lai, Man-Hung Siu:
High-density discrete HMM with the use of scalar quantization indexing. INTERSPEECH 2005: 2121-2124 - 2004
- [j7]Brian Mak:
An Acoustic-Phonetic and a Model-Theoretic Analysis of Subspace Distribution Clustering Hidden Markov Models. Int. J. Speech Technol. 7(1): 55-68 (2004) - [j6]Brian Kan-Wing Mak, Yik-Cheung Tam, Peter Qi Li:
Discriminative auditory-based features for robust speech recognition. IEEE Trans. Speech Audio Process. 12(1): 27-36 (2004) - [c26]Brian Mak, James T. Kwok, Simon Ka-Lung Ho:
A study of various composite kernels for kernel eigenvoice speaker adaptation. ICASSP (1) 2004: 325-328 - [c25]Roger Hsiao, Brian Mak:
Discriminative feature transformation by guided discriminative training. ICASSP (1) 2004: 897-900 - [c24]Brian Kan-Wing Mak, Roger Wend-Huu Hsiao:
Improving eigenspace-based MLLR adaptation by kernel PCA. INTERSPEECH 2004: 13-16 - [c23]Brian Mak, Simon Ka-Lung Ho, James T. Kwok:
Speedup of kernel eigenvoice speaker adaptation by embedded kernel PCA. INTERSPEECH 2004: 2913-2916 - 2003
- [c22]Brian Mak, Yik-Cheung Tam, Roger Hsiao:
Discriminative training of auditory filters of different shapes for robust speech recognition. ICASSP (2) 2003: 45-48 - [c21]Simon Ka-Lung Ho, Brian Mak:
Joint estimation of thresholds in a bi-threshold verification problem. INTERSPEECH 2003: 893-896 - [c20]Brian Kan-Wing Mak, Kin-Wah Chan:
Pruning transitions in a hidden Markov model with optimal brain surgeon. INTERSPEECH 2003: 2521-2524 - [c19]James T. Kwok, Brian Mak, Simon Ka-Lung Ho:
Eigenvoice Speaker Adaptation via Composite Kernel PCA. NIPS 2003: 1401-1408 - 2002
- [j5]Brian Mak:
A mathematical relationship between full-band and multiband mel-frequency cepstral coefficients. IEEE Signal Process. Lett. 9(8): 241-244 (2002) - [c18]Yik-Cheung Tam, Brian Mak:
An alternative approach of finding competing hypotheses for better minimum classification error training. ICASSP 2002: 101-104 - [c17]Brian Mak, Yik-Cheung Tam, Peter Qi Li:
Discriminative auditory features for robust speech recognition. ICASSP 2002: 381-384 - [c16]Brian Kan-Wing Mak, Yik-Cheung Tam:
Performance of discriminatively trained auditory features on Aurora2 and Aurora3. INTERSPEECH 2002: 33-36 - [c15]Kok-Wee Gan, Chi-Yung Wang, Brian Mak:
Knowledge-based sense pruning using the hownet: an alternative to word sense disambiguation. ISCSLP 2002 - 2001
- [j4]Enrico Bocchieri, Brian Kan-Wing Mak:
Subspace distribution clustering hidden Markov model. IEEE Trans. Speech Audio Process. 9(3): 264-275 (2001) - [j3]Brian Kan-Wing Mak, Enrico Bocchieri:
Direct training of subspace distribution clustering hidden Markov model. IEEE Trans. Speech Audio Process. 9(4): 378-387 (2001) - [c14]Yik-Cheung Tam, Brian Kan-Wing Mak:
Development of an asynchronous multi-band system for continuous speech recognition. INTERSPEECH 2001: 575-578 - [c13]Kwok-Man Wong, Brian Kan-Wing Mak:
Rapid speaker adaptation using MLLR and subspace regression classes. INTERSPEECH 2001: 1253-1256 - 2000
- [c12]Kwok-Man Wong, Brian Mak:
MAP adaptation with subspace regression classes and tying. ICASSP 2000: 1551-1554 - [c11]Brian Kan-Wing Mak, Yik-Cheung Tam:
Asynchrony with trained transition probabilities improves performance in multi-band speech recognition. INTERSPEECH 2000: 149-152 - [c10]Yu-Chung Chan, Man-Hung Siu, Brian Kan-Wing Mak:
Pruning of state-tying tree using bayesian information criterion with multiple mixtures. INTERSPEECH 2000: 294-297 - [c9]Yik-Cheung Tam, Brian Kan-Wing Mak:
Optimization of sub-band weights using simulated noisy speech in multi-band speech recognition. INTERSPEECH 2000: 313-316
1990 – 1999
- 1998
- [c8]Brian Mak, Enrico Bocchieri:
Training of subspace distribution clustering hidden Markov model. ICASSP 1998: 673-676 - [c7]Brian Mak, Enrico Bocchieri:
Training of context-dependent subspace distribution clustering hidden Markov model. ICSLP 1998 - 1997
- [c6]Brian Mak:
Combining ANNs to improve phone recognition. ICASSP 1997: 3253-3256 - [c5]Enrico Bocchieri, Brian Mak:
Subspace distribution clustering for continuous observation density hidden Markov models. EUROSPEECH 1997: 107-110 - 1996
- [c4]Ronald A. Cole, Yonghong Yan, Brian Mak, Mark A. Fanty, Troy Bailey:
The contribution of consonants versus vowels to word recognition in fluent speech. ICASSP 1996: 853-856 - [c3]Brian Mak, Etienne Barnard:
Phone clustering using the bhattacharyya distance. ICSLP 1996: 2005-2008 - 1995
- [j2]Tan Lee, P. C. Ching, Lai-Wan Chan, Y. H. Cheng, Brian Mak:
Tone recognition of isolated Cantonese syllables. IEEE Trans. Speech Audio Process. 3(3): 204-209 (1995) - 1994
- [j1]Jean-Claude Junqua, Brian Mak, Ben Reaves:
A robust algorithm for word boundary detection in the presence of noise. IEEE Trans. Speech Audio Process. 2(3): 406-412 (1994) - 1992
- [c2]Brian Mak, Jean-Claude Junqua, Ben Reaves:
A robust speech/non-speech detection algorithm using time and frequency-based features. ICASSP 1992: 269-272 - 1991
- [c1]Jean-Claude Junqua, Ben Reaves, Brian Mak:
A study of endpoint detection algorithms in adverse conditions: incidence on a DTW and HMM recognizer. EUROSPEECH 1991: 1371-1374
Coauthor Index
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