| Long short term memory recurrent neural network based multimodal dimensional emotion recognition L Chao, J Tao, M Yang, Y Li, Z Wen Proceedings of the 5th international workshop on audio/visual emotion …, 2015 | 172 | 2015 |
| CHEAVD: a Chinese natural emotional audio–visual database Y Li, J Tao, L Chao, W Bao, Y Liu Journal of Ambient Intelligence and Humanized Computing 8, 913-924, 2017 | 117 | 2017 |
| Continuous multimodal emotion prediction based on long short term memory recurrent neural network J Huang, Y Li, J Tao, Z Lian, Z Wen, M Yang, J Yi Proceedings of the 7th Annual Workshop on Audio/Visual Emotion Challenge, 11-18, 2017 | 70 | 2017 |
| Expression analysis based on face regions in real-world conditions Z Lian, Y Li, JH Tao, J Huang, MY Niu International Journal of Automation and Computing 17, 96-107, 2020 | 61 | 2020 |
| Speech emotion recognition via contrastive loss under siamese networks Z Lian, Y Li, J Tao, J Huang Proceedings of the Joint Workshop of the 4th Workshop on Affective Social …, 2018 | 60 | 2018 |
| Mec 2017: Multimodal emotion recognition challenge Y Li, J Tao, B Schuller, S Shan, D Jiang, J Jia 2018 First Asian Conference on Affective Computing and Intelligent …, 2018 | 56 | 2018 |
| Multi task sequence learning for depression scale prediction from video L Chao, J Tao, M Yang, Y Li 2015 International conference on affective computing and intelligent …, 2015 | 56 | 2015 |
| Multi-scale temporal modeling for dimensional emotion recognition in video L Chao, J Tao, M Yang, Y Li, Z Wen Proceedings of the 4th international workshop on audio/visual emotion …, 2014 | 46 | 2014 |
| MEC 2016: the multimodal emotion recognition challenge of CCPR 2016 Y Li, J Tao, B Schuller, S Shan, D Jiang, J Jia Pattern Recognition: 7th Chinese Conference, CCPR 2016, Chengdu, China …, 2016 | 45 | 2016 |
| Semi-supervised ladder networks for speech emotion recognition JH Tao, J Huang, Y Li, Z Lian, MY Niu International Journal of Automation and Computing 16, 437-448, 2019 | 43 | 2019 |
| Multimodal continuous emotion recognition with data augmentation using recurrent neural networks J Huang, Y Li, J Tao, Z Lian, M Niu, M Yang Proceedings of the 2018 on audio/visual emotion challenge and workshop, 57-64, 2018 | 43 | 2018 |
| Long short term memory recurrent neural network based encoding method for emotion recognition in video L Chao, J Tao, M Yang, Y Li, Z Wen 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 42 | 2016 |
| A novel method of artificial bandwidth extension using deep architecture. B Liu, J Tao, Z Wen, Y Li, D Bukhari INTERSPEECH, 2598-2602, 2015 | 40 | 2015 |
| Building a chinese natural emotional audio-visual database W Bao, Y Li, M Gu, M Yang, H Li, L Chao, J Tao 2014 12th International conference on signal processing (ICSP), 583-587, 2014 | 39 | 2014 |
| Speech emotion recognition using semi-supervised learning with ladder networks J Huang, Y Li, J Tao, Z Lian, M Niu, J Yi 2018 First Asian conference on affective computing and intelligent …, 2018 | 36 | 2018 |
| Distilling Knowledge from an Ensemble of Models for Punctuation Prediction. J Yi, J Tao, Z Wen, Y Li Interspeech, 2779-2783, 2017 | 35 | 2017 |
| Audio visual emotion recognition with temporal alignment and perception attention L Chao, J Tao, M Yang, Y Li, Z Wen arXiv preprint arXiv:1603.08321, 2016 | 35 | 2016 |
| End-to-end continuous emotion recognition from video using 3D ConvLSTM networks J Huang, Y Li, J Tao, Z Lian, J Yi 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 32 | 2018 |
| BLSTM-CRF Based End-to-End Prosodic Boundary Prediction with Context Sensitive Embeddings in a Text-to-Speech Front-End. Y Zheng, J Tao, Z Wen, Y Li Interspeech, 47-51, 2018 | 31 | 2018 |
| End-to-end keywords spotting based on connectionist temporal classification for mandarin Y Bai, J Yi, H Ni, Z Wen, B Liu, Y Li, J Tao 2016 10th international symposium on Chinese spoken language processing …, 2016 | 30 | 2016 |
Björn SchullerProfessor, Technische Universität München (TUM) / Imperial College London & CSO, audEERING在 tum.de 的电子邮件经过验证
