Wen Wang
- Artificial Intelligence top 1%
- Signal Processing top 5%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 10%
- Experimental and Cognitive Psychology
- Co-authors
- Jing ZhengAndreas StolckeMary P. HarperDimitra VergyriHongyuan ZhaXinyin MaWeiming LüYongliang Shen
- Topics
- Natural Language Processing Techniques (45 papers)Topic Modeling (36 papers)Speech Recognition and Synthesis (29 papers)
- Partner nations
- United StatesChinaCayman Islands
In The Last Decade
Wen Wang
67 papers receiving 964 citations
Peers
Comparison fields: 5 of 90
- Artificial Intelligence 912
- Signal Processing 232
- Computer Vision and Pattern Recognition 167
- Information Systems 95
- Experimental and Cognitive Psychology 67
Countries citing papers authored by Wen Wang
This map shows the geographic impact of Wen Wang'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 Wen Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wen Wang more than expected).
Fields of papers citing papers by Wen Wang
This network shows the impact of papers produced by Wen Wang. 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 Wen Wang. The network helps show where Wen Wang may publish in the future.
Co-authorship network of co-authors of Wen Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Wen Wang. A scholar is included among the top collaborators of Wen Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Wen Wang. Wen Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 17 | |
| 9 | 1 | |
| 10 | 110 | |
| 11 | 55 | |
| 12 | A Cross-language Study on Automatic Speech Disfluency Detection | 4 |
| 13 | Name-aware Machine Translation | 7 |
| 14 | Articulatory features for large vocabulary speech recognition | 5 |
| 15 | N-Best Rescoring Based on Pitch-accent Patterns | 5 |
| 16 | Detection of Agreement and Disagreement in Broadcast Conversations | 16 |
| 17 | 18 | |
| 18 | 2 | |
| 19 | 17 | |
| 20 | Mandarin Part-of-Speech Tagging and Discriminative Reranking | 31 |
About Wen Wang
Wen Wang is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition, having authored 70 papers that have together received 1.1k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (45 papers), Topic Modeling (36 papers) and Speech Recognition and Synthesis (29 papers). The work is most often cited by research in Artificial Intelligence (912 citations), Signal Processing (232 citations) and Computer Vision and Pattern Recognition (167 citations). Wen Wang has collaborated with scholars based in United States, China and Cayman Islands. Frequent co-authors include Jing Zheng, Andreas Stolcke, Mary P. Harper, Dimitra Vergyri, Hongyuan Zha, Xinyin Ma, Weiming Lü, Yongliang Shen, Shuai Zhang and Wei Zhang. Their work appears in journals such as IEEE Access, Sensors and IEEE Signal Processing Magazine.
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.