Jun Du

9.7k citations

329 papers · 6.2k indexed · 2 hit papers · h-index 36

Impact in

Signal Processing top 0.05%
- Speech and Audio Processing
- Music and Audio Processing
- Blind Source Separation Techniques
Artificial Intelligence top 0.2%
- Speech Recognition and Synthesis
- Natural Language Processing Techniques

Papers in ⓘ

Signal Processing 163
- Speech and Audio Processing 154
- Music and Audio Processing 101
Artificial Intelligence 149
- Speech Recognition and Synthesis 112
- Natural Language Processing Techniques 16

Co-authors: Chin‐Hui Lee (106 shared papers)Li-Rong Dai (57 shared papers)Yong Xu (12 shared papers)Jianshu Zhang (25 shared papers)Yan-Hui Tu (25 shared papers)Zi-Rui Wang (15 shared papers)Xiaohu Wen (1 shared paper)Zhibin He (1 shared paper)
Journals: IEEE/ACM Transactions on Audio Speech and Language Processing (21 papers)Pattern Recognition (17 papers)IEEE Transactions on Multimedia (5 papers)Polymer Chemistry (3 papers)Remote Sensing (3 papers)
Partner nations: China United States Italy

In The Last Decade

Jun Du

305 papers receiving 5.8k citations

Hit Papers

align trajectories log scale

A Regression Approach to Speech Enhancement Based on Deep Neural Networks 2014 · 935 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2014 IEEE/ACM Transactions on Audio Speech and Language Processing
2013 IEEE Signal Processing Letters

Peers

Countries citing papers authored by Jun Du

Since Specialization

Citations

This map shows the geographic impact of Jun Du's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jun Du with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Du more than expected).

Fields of papers citing papers by Jun Du

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun Du. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jun Du. The network helps show where Jun Du may publish in the future.

Co-authors

The 25 scholars most cited alongside Jun Du, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jun Du Line = papers co-authored together Jun Du links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 329 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	A Regression Approach to Speech Enhancement Based on Deep Neural Networks IEEE/ACM Transactions on Audio Speech and Language Processing ·Yong Xu, Jun Du, Li-Rong Dai, Chin‐Hui Lee Hit paper breakdown →	2014	935
2	An Experimental Study on Speech Enhancement Based on Deep Neural Networks IEEE Signal Processing Letters ·Yong Xu, Jun Du, Li-Rong Dai, Chin‐Hui Lee Hit paper breakdown →	2013	676
3	A comparative study of artificial neural network, adaptive neuro fuzzy inference system and support vector machine for forecasting river flow in the semiarid mountain region Journal of Hydrology ·Zhibin He, Xiaohu Wen, Hu Liu, Jun Du	2013	291
4	Multiple-target deep learning for LSTM-RNN based speech enhancement Lei Sun, Jun Du, Li-Rong Dai, Chin‐Hui Lee	2017	157
5	Watch, attend and parse: An end-to-end neural network based approach to handwritten mathematical expression recognition Pattern Recognition ·Jianshu Zhang, Jun Du, Shiliang Zhang, Dan Liu, Yulong Hu, Jinshui Hu, Si Wei, Li-Rong Dai	2017	125
6	Colored Radiative Cooler under Optical Tamm Resonance ACS Photonics ·Chunxiang Sheng, Yidan An, Jun Du, Xiaofeng Li	2019	96
7	A speech enhancement approach using piecewise linear approximation of an explicit model of environmental distortions Jun Du, Qiang Huo	2008	83
8	TextMountain: Accurate scene text detection via instance segmentation Pattern Recognition ·Yixing Zhu, Jun Du	2020	78
9	A Regression Approach to Single-Channel Speech Separation Via High-Resolution Deep Neural Networks IEEE/ACM Transactions on Audio Speech and Language Processing ·Jun Du, Yan-Hui Tu, Li-Rong Dai, Chin‐Hui Lee	2016	77
10	Robust speech recognition with speech enhanced deep neural networks Jun Du, Qing Wang, Tian Gao, Yong Xu, Li-Rong Dai, Chin‐Hui Lee	2014	75
11	Track, Attend, and Parse (TAP): An End-to-End Framework for Online Handwritten Mathematical Expression Recognition IEEE Transactions on Multimedia ·Jianshu Zhang, Jun Du, Li-Rong Dai	2018	74
12	Multi-Scale Attention with Dense Encoder for Handwritten Mathematical Expression Recognition Jianshu Zhang, Jun Du, Li-Rong Dai	2018	71
13	Speech Enhancement Based on Teacher–Student Deep Learning Using Improved Speech Presence Probability for Noise-Robust Speech Recognition IEEE/ACM Transactions on Audio Speech and Language Processing ·Yan-Hui Tu, Jun Du, Chin‐Hui Lee	2019	70
14	Multi-objective learning and mask-based post-processing for deep neural network based speech enhancement Yong Xu, Jun Du, Zhen Huang, Li-Rong Dai, Chin‐Hui Lee	2015	69
15	RORα, a Potential Tumor Suppressor and Therapeutic Target of Breast Cancer International Journal of Molecular Sciences ·Jun Du, Ren Xu	2012	67
16	SNR-Based Progressive Learning of Deep Neural Network for Speech Enhancement Tian Gao, Jun Du, Li-Rong Dai, Chin‐Hui Lee	2016	64
17	Dynamic noise aware training for speech enhancement based on deep neural networks Yong Xu, Jun Du, Li-Rong Dai, Chin‐Hui Lee	2014	62
18	Densely Connected Progressive Learning for LSTM-Based Speech Enhancement Tian Gao, Jun Du, Li-Rong Dai, Chin‐Hui Lee	2018	60
19	Speech separation of a target speaker based on deep neural networks Jun Du, Yan-Hui Tu, Yong Xu, Li-Rong Dai, Chin‐Hui Lee	2014	60
20	Joint training of front-end and back-end deep neural networks for robust speech recognition Tian Gao, Jun Du, Li-Rong Dai, Chin‐Hui Lee	2015	56

About Jun Du

Jun Du is a scholar working on Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics and Computational Mathematics, having authored 329 papers that have together received 6.2k indexed citations. Recurring topics across this work include Speech and Audio Processing (154 papers), Speech Recognition and Synthesis (112 papers), Music and Audio Processing (101 papers), Handwritten Text Recognition Techniques (46 papers), Advanced Adaptive Filtering Techniques (41 papers), Natural Language Processing Techniques (16 papers), Image Processing and 3D Reconstruction (15 papers) and Hearing Loss and Rehabilitation (13 papers). The work is most often cited by research in Signal Processing (3.5k citations), Artificial Intelligence (2.8k citations), Computer Vision and Pattern Recognition (1.3k citations), Computational Mechanics (1.2k citations) and Cognitive Neuroscience (612 citations). Jun Du has collaborated with scholars based in China, United States and Italy. Frequent co-authors include Chin‐Hui Lee, Li-Rong Dai, Yong Xu, Jianshu Zhang, Yan-Hui Tu, Zi-Rui Wang, Xiaohu Wen, Zhibin He, Hu Liu and Lei Sun. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, Pattern Recognition, IEEE Transactions on Multimedia, Polymer Chemistry and Remote Sensing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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