Minghui Dong
Impact in
- Signal Processing top 2%
- Speech and Audio Processing
- Music and Audio Processing
- Artificial Intelligence top 2%
- Speech Recognition and Synthesis
- Natural Language Processing Techniques
- Topic Modeling
Papers in
-
- Speech Recognition and Synthesis 40
- Natural Language Processing Techniques 12
- Speech and dialogue systems 4
-
- Speech and Audio Processing 40
- Music and Audio Processing 28
- Co-authors
- Haizhou Li (44 shared papers)Shiping Wen (2 shared papers)Zhigang Zeng (2 shared papers)Pan Zhou (2 shared papers)Dongyan Huang (10 shared papers)Zhuoling Li (1 shared paper)Xiang Hu (1 shared paper)Tingwen Huang (2 shared papers)
In The Last Decade
Minghui Dong
74 papers receiving 848 citations
Peers
Comparison fields: 5 of 113
- Signal Processing 326
- Artificial Intelligence 490
- Experimental and Cognitive Psychology 160
- Computer Vision and Pattern Recognition 211
- Statistical and Nonlinear Physics 49
Countries citing papers authored by Minghui Dong
This map shows the geographic impact of Minghui Dong'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 Minghui Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minghui Dong more than expected).
Fields of papers citing papers by Minghui Dong
This network shows the impact of papers produced by Minghui Dong. 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 Minghui Dong. The network helps show where Minghui Dong may publish in the future.
Co-authors
The 25 scholars most cited alongside Minghui Dong, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 151 | |
| 2 | 2018 | 61 | |
| 3 | 2019 | 59 | |
| 4 | 2016 | 52 | |
| 5 | Semantic Transliteration of Personal Names | 2007 | 34 |
| 6 | 2017 | 31 | |
| 7 | 2019 | 30 | |
| 8 | 2016 | 29 | |
| 9 | 2019 | 26 | |
| 10 | 2016 | 25 | |
| 11 | 2015 | 23 | |
| 12 | 2000 | 22 | |
| 13 | 2019 | 21 | |
| 14 | 2014 | 19 | |
| 15 | 2012 | 17 | |
| 16 | 2010 | 17 | |
| 17 | 2015 | 16 | |
| 18 | 2006 | 16 | |
| 19 | 2015 | 14 | |
| 20 | 2017 | 12 |
About Minghui Dong
Minghui Dong is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Electrical and Electronic Engineering, having authored 79 papers that have together received 907 indexed citations. Recurring topics across this work include Speech and Audio Processing (40 papers), Speech Recognition and Synthesis (40 papers), Music and Audio Processing (28 papers), Natural Language Processing Techniques (12 papers), Emotion and Mood Recognition (7 papers), Face recognition and analysis (5 papers), Face and Expression Recognition (4 papers) and Speech and dialogue systems (4 papers). The work is most often cited by research in Signal Processing (326 citations), Artificial Intelligence (490 citations), Experimental and Cognitive Psychology (160 citations), Computer Vision and Pattern Recognition (211 citations) and Statistical and Nonlinear Physics (49 citations). Minghui Dong has collaborated with scholars based in Singapore, China and Canada. Frequent co-authors include Haizhou Li, Shiping Wen, Zhigang Zeng, Pan Zhou, Dongyan Huang, Zhuoling Li, Xiang Hu, Tingwen Huang, Dongyan Huang and Lei Xie. Their work appears in journals such as Neurocomputing, Applied Physics A, Research, Analytical Methods and Advances in Space Research.
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.