Jiangyan Yi
Impact in
- Signal Processing top 1%
- Speech and Audio Processing
- Music and Audio Processing
- Artificial Intelligence top 2%
- Speech Recognition and Synthesis
- Natural Language Processing Techniques
- Topic Modeling
- Speech and dialogue systems
Papers in
-
- Speech Recognition and Synthesis 71
- Natural Language Processing Techniques 22
- Topic Modeling 13
- Speech and dialogue systems 5
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- Speech and Audio Processing 60
- Music and Audio Processing 59
- Co-authors
- Jianhua Tao (86 shared papers)Zhengqi Wen (50 shared papers)Ye Bai (26 shared papers)Zhengkun Tian (20 shared papers)Cunhang Fan (30 shared papers)Ruibo Fu (25 shared papers)Bin Liu (5 shared papers)Ya Li (6 shared papers)
In The Last Decade
Jiangyan Yi
96 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 78
- Signal Processing 716
- Artificial Intelligence 855
- Computer Vision and Pattern Recognition 255
- Experimental and Cognitive Psychology 127
- Cognitive Neuroscience 51
Countries citing papers authored by Jiangyan Yi
This map shows the geographic impact of Jiangyan Yi'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 Jiangyan Yi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiangyan Yi more than expected).
Fields of papers citing papers by Jiangyan Yi
This network shows the impact of papers produced by Jiangyan Yi. 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 Jiangyan Yi. The network helps show where Jiangyan Yi may publish in the future.
Co-authors
The 25 scholars most cited alongside Jiangyan Yi, 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 104 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 98 | |
| 2 | 2020 | 75 | |
| 3 | 2021 | 52 | |
| 4 | 2020 | 42 | |
| 5 | 2017 | 40 | |
| 6 | 2018 | 38 | |
| 7 | 2021 | 37 | |
| 8 | 2023 | 34 | |
| 9 | 2020 | 34 | |
| 10 | 2019 | 33 | |
| 11 | 2020 | 31 | |
| 12 | 2020 | 29 | |
| 13 | 2018 | 27 | |
| 14 | 2023 | 22 | |
| 15 | 2022 | 22 | |
| 16 | 2017 | 20 | |
| 17 | 2018 | 20 | |
| 18 | 2018 | 20 | |
| 19 | 2019 | 20 | |
| 20 | 2019 | 18 |
About Jiangyan Yi
Jiangyan Yi is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Information Systems, having authored 104 papers that have together received 1.2k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (71 papers), Speech and Audio Processing (60 papers), Music and Audio Processing (59 papers), Natural Language Processing Techniques (22 papers), Digital Media Forensic Detection (18 papers), Topic Modeling (13 papers), Speech and dialogue systems (5 papers) and Emotion and Mood Recognition (5 papers). The work is most often cited by research in Signal Processing (716 citations), Artificial Intelligence (855 citations), Computer Vision and Pattern Recognition (255 citations), Experimental and Cognitive Psychology (127 citations) and Cognitive Neuroscience (51 citations). Jiangyan Yi has collaborated with scholars based in China, Singapore and Hong Kong. Frequent co-authors include Jianhua Tao, Zhengqi Wen, Ye Bai, Zhengkun Tian, Cunhang Fan, Ruibo Fu, Bin Liu, Ya Li, Shuai Zhang and Zheng Lian. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, Speech Communication, Applied Acoustics, IEEE Signal Processing Letters and Neural Networks.
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.