| Morphological and acoustical analysis of the nasal and the paranasal cavities J Dang, K Honda, H Suzuki The Journal of the Acoustical Society of America 96 (4), 2088-2100, 1994 | 219 | 1994 |
| Acoustic characteristics of the piriform fossa in models and humans J Dang, K Honda The Journal of the Acoustical Society of America 101 (1), 456-465, 1997 | 217 | 1997 |
| Construction and control of a physiological articulatory model J Dang, K Honda The Journal of the Acoustical Society of America 115 (2), 853-870, 2004 | 209 | 2004 |
| An investigation of dependencies between frequency components and speaker characteristics for text-independent speaker identification X Lu, J Dang Speech communication 50 (4), 312-322, 2008 | 162 | 2008 |
| Voice activity detection based on an unsupervised learning framework D Ying, Y Yan, J Dang, FK Soong IEEE Transactions on Audio, Speech, and Language Processing 19 (8), 2624-2633, 2011 | 150 | 2011 |
| Spex+: A complete time domain speaker extraction network M Ge, C Xu, L Wang, ES Chng, J Dang, H Li arXiv preprint arXiv:2005.04686, 2020 | 128 | 2020 |
| Multi-kernel SVM based depression recognition using social media data Z Peng, Q Hu, J Dang International Journal of Machine Learning and Cybernetics 10, 43-57, 2019 | 114 | 2019 |
| Acoustic characteristics of the human paranasal sinuses derived from transmission characteristic measurement and morphological observation J Dang, K Honda The Journal of the Acoustical Society of America 100 (5), 3374-3383, 1996 | 100 | 1996 |
| Estimation of vocal tract shapes from speech sounds with a physiological articulatory model J Dang, K Honda Journal of Phonetics 30 (3), 511-532, 2002 | 91 | 2002 |
| Relation modeling with graph convolutional networks for facial action unit detection Z Liu, J Dong, C Zhang, L Wang, J Dang MultiMedia Modeling: 26th International Conference, MMM 2020, Daejeon, South …, 2020 | 75 | 2020 |
| Speech emotion recognition using 3d convolutions and attention-based sliding recurrent networks with auditory front-ends Z Peng, X Li, Z Zhu, M Unoki, J Dang, M Akagi IEEE Access 8, 16560-16572, 2020 | 70 | 2020 |
| Incorporating network structure with node contents for community detection on large networks using deep learning J Cao, D Jin, L Yang, J Dang Neurocomputing 297, 71-81, 2018 | 65 | 2018 |
| Fuzzy rough regression with application to wind speed prediction S An, H Shi, Q Hu, X Li, J Dang Information Sciences 282, 388-400, 2014 | 63 | 2014 |
| Integration of articulatory and spectrum features based on the hybrid HMM/BN modeling framework K Markov, J Dang, S Nakamura Speech Communication 48 (2), 161-175, 2006 | 62 | 2006 |
| A feature fusion method based on extreme learning machine for speech emotion recognition L Guo, L Wang, J Dang, L Zhang, H Guan 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 60 | 2018 |
| A computational tongue model and its clinical application S Fujita, J Dang, N Suzuki, K Honda Oral Science International 4 (2), 97-109, 2007 | 60 | 2007 |
| Exploration of complementary features for speech emotion recognition based on kernel extreme learning machine L Guo, L Wang, J Dang, Z Liu, H Guan IEEE Access 7, 75798-75809, 2019 | 59 | 2019 |
| Improved support vector machine algorithm for heterogeneous data S Peng, Q Hu, Y Chen, J Dang Pattern Recognition 48 (6), 2072-2083, 2015 | 58 | 2015 |
| Speech emotion recognition with local-global aware deep representation learning J Liu, Z Liu, L Wang, L Guo, J Dang ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 57 | 2020 |
| Combined node and link partitions method for finding overlapping communities in complex networks D Jin, B Gabrys, J Dang Scientific reports 5 (1), 8600, 2015 | 57 | 2015 |
Longbiao WangProfessor, Tianjin University在 tju.edu.cn 的电子邮件经过验证
