| Parallel inference of dirichlet process Gaussian mixture models for unsupervised acoustic modeling: a feasibility study. H Chen, CC Leung, L Xie, B Ma, H Li INTERSPEECH 15, 3189-3193, 2015 | 87 | 2015 |
| Constrained MLLR for speaker recognition M Ferras, CC Leung, C Barras, JL Gauvain 2007 IEEE International Conference on Acoustics, Speech and Signal …, 2007 | 87 | 2007 |
| 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 | 82 | 2014 |
| Acoustic segment modeling with spectral clustering methods H Wang, T Lee, CC Leung, B Ma, H Li IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (2), 264-277, 2015 | 69 | 2015 |
| An acoustic segment modeling approach to query-by-example spoken term detection H Wang, CC Leung, T Lee, B Ma, H Li 2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012 | 69 | 2012 |
| Using parallel tokenizers with DTW matrix combination for low-resource spoken term detection H Wang, T Lee, CC Leung, B Ma, H Li 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 60 | 2013 |
| Shifted-delta MLP features for spoken language recognition H Wang, CC Leung, T Lee, B Ma, H Li IEEE Signal Processing Letters 20 (1), 15-18, 2012 | 57 | 2012 |
| Comparison of speaker adaptation methods as feature extraction for SVM-based speaker recognition M Ferras, CC Leung, C Barras, JL Gauvain IEEE Transactions on Audio, Speech, and Language Processing 18 (6), 1366-1378, 2009 | 54 | 2009 |
| Low-resource keyword search strategies for Tamil NF Chen, C Ni, IF Chen, S Sivadas, H Xu, X Xiao, TS Lau, SJ Leow, ... 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 44 | 2015 |
| Unsupervised Bottleneck Features for Low-Resource Query-by-Example Spoken Term Detection. H Chen, CC Leung, L Xie, B Ma, H Li Interspeech, 923-927, 2016 | 42 | 2016 |
| Unsupervised spoken term detection with acoustic segment model H Wang, T Lee, CC Leung 2011 International Conference on Speech Database and Assessments (Oriental …, 2011 | 39 | 2011 |
| Learning acoustic word embeddings with temporal context for query-by-example speech search Y Yuan, CC Leung, L Xie, H Chen, B Ma, H Li arXiv preprint arXiv:1806.03621, 2018 | 37 | 2018 |
| Multilingual bottle-neck feature learning from untranscribed speech H Chen, CC Leung, L Xie, B Ma, H Li 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU …, 2017 | 36 | 2017 |
| Pairwise learning using multi-lingual bottleneck features for low-resource query-by-example spoken term detection Y Yuan, CC Leung, L Xie, H Chen, B Ma, H Li 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 31 | 2017 |
| Unsupervised data selection and word-morph mixed language model for tamil low-resource keyword search C Ni, CC Leung, L Wang, NF Chen, B Ma 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 31 | 2015 |
| Prosodic attribute model for spoken language identification RWM Ng, CC Leung, T Lee, B Ma, H Li 2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010 | 31 | 2010 |
| Spoken Language Recognition with Prosodic Features RWM Ng, T Lee, CC Leung, B Ma, H Li IEEE, 2013 | 30 | 2013 |
| Unsupervised mining of acoustic subword units with segment-level Gaussian posteriorgrams. H Wang, T Lee, CC Leung, B Ma, H Li INTERSPEECH, 2297-2301, 2013 | 28 | 2013 |
| Intrinsic spectral analysis based on temporal context features for query-by-example spoken term detection P Yang, CC Leung, L Xie, B Ma, H Li Fifteenth Annual Conference of the International Speech Communication …, 2014 | 26 | 2014 |
| Fixed-point GMM-based speaker verification over mobile embedded system YS Moon, CC Leung, KH Pun Proceedings of the 2003 ACM SIGMM workshop on Biometrics methods and …, 2003 | 26 | 2003 |
Haizhou LiThe Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), China; NUS, Singapore在 u.nus.edu 的电子邮件经过验证
