| A Regression Approach to Speech Enhancement Based on Deep Neural Networks Y Xu, J Du, LR Dai, CH Lee IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (1), 7 - 19, 2015 | 1292 | 2015 |
| An experimental study on speech enhancement based on deep neural networks Y Xu, J Du, LR Dai, CH Lee IEEE Signal processing letters 21 (1), 65-68, 2014 | 947 | 2014 |
| Large-scale weakly supervised audio classification using gated convolutional neural network Yong Xu, Qiuqiang Kong, Wenwu Wang, Mark D. Plumbley ICASSP2018, 2018 | 248* | 2018 |
| An overview of deep-learning-based audio-visual speech enhancement and separation D Michelsanti, ZH Tan, SX Zhang, Y Xu, M Yu, D Yu, J Jensen IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2021 | 137 | 2021 |
| Multi-Objective Learning and Mask-Based Post-Processing for Deep Neural Network Based Speech Enhancement Y Xu, J Du, Z Huang, LR Dai, CH Lee Interspeech2015, 2015 | 122 | 2015 |
| Robust speech recognition with speech enhanced deep neural networks. J Du, Q Wang, T Gao, Y Xu, LR Dai, CH Lee INTERSPEECH, 616-620, 2014 | 121 | 2014 |
| Audio set classification with attention model: A probabilistic perspective Q Kong, Y Xu, W Wang, MD Plumbley 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 113 | 2018 |
| Convolutional Gated Recurrent Neural Network Incorporating Spatial Features for Audio Tagging Yong Xu, Qiuqiang Kong, Qiang Huang, Wenwu Wang, Mark D. Plumbley IJCNN2017, 2017 | 109* | 2017 |
| Sound Event Detection and Time–Frequency Segmentation from Weakly Labelled Data Q Kong, Y Xu, I Sobieraj, W Wang, MD Plumbley IEEE/ACM Transactions on Audio, Speech, and Language Processing 27 (4), 777-787, 2019 | 107 | 2019 |
| Sound event detection of weakly labelled data with CNN-transformer and automatic threshold optimization Q Kong, Y Xu, W Wang, MD Plumbley IEEE/ACM Transactions on Audio, Speech, and Language Processing 28, 2450-2460, 2020 | 96 | 2020 |
| Dynamic noise aware training for speech enhancement based on deep neural networks. Y Xu, J Du, LR Dai, CH Lee INTERSPEECH, 2670-2674, 2014 | 94 | 2014 |
| Unsupervised feature learning based on deep models for environmental audio tagging Y Xu, Q Huang, W Wang, P Foster, S Sigtia, PJB Jackson, MD Plumbley IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (6), 1230 …, 2017 | 92 | 2017 |
| Weakly Labelled AudioSet Tagging With Attention Neural Networks Q Kong, C Yu, Y Xu, T Iqbal, W Wang, MD Plumbley IEEE/ACM Transactions on Audio, Speech, and Language Processing 27 (11 …, 2019 | 88 | 2019 |
| Cross-task learning for audio tagging, sound event detection and spatial localization: DCASE 2019 baseline systems Q Kong, Y Cao, T Iqbal, Y Xu, W Wang, MD Plumbley arXiv preprint arXiv:1904.03476, 2019 | 85 | 2019 |
| Speech separation of a target speaker based on deep neural networks J Du, Y Tu, Y Xu, L Dai, CH Lee 2014 12th International Conference on Signal Processing (ICSP), 473-477, 2014 | 78 | 2014 |
| Time domain audio visual speech separation J Wu, Y Xu, SX Zhang, LW Chen, M Yu, L Xie, D Yu 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU …, 2019 | 76 | 2019 |
| ADL-MVDR: All deep learning MVDR beamformer for target speech separation Z Zhang, Y Xu, M Yu, SX Zhang, L Chen, D Yu ICASSP2021, 2020 | 75 | 2020 |
| A comprehensive study of speech separation: spectrogram vs waveform separation F Bahmaninezhad, J Wu, R Gu, SX Zhang, Y Xu, M Yu, D Yu Interspeech2019, 2019 | 74 | 2019 |
| Neural Spatial Filter: Target Speaker Speech Separation Assisted with Directional Information. R Gu, L Chen, SX Zhang, J Zheng, Y Xu, M Yu, D Su, Y Zou, D Yu Interspeech, 4290-4294, 2019 | 72 | 2019 |
| Multi-modal Multi-channel Target Speech Separation Rongzhi Gu, Shi-Xiong Zhang, Yong Xu, Lianwu Chen, Yuexian Zou, Dong Yu IEEE Journal of Selcted Topics in Signal Processing, 2020 | 71* | 2020 |
Wenwu WangProfessor, University of Surrey, UKVerified email at surrey.ac.uk
