Runsheng Liu
- Signal Processing top 2%
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Computational Mechanics top 10%
- Cognitive Neuroscience
- Co-authors
- Yi JiangDeLiang WangZhenming FengJia LiuMin ChuYining ChenEric ChangDong Wang
- Topics
- Speech and Audio Processing (23 papers)Speech Recognition and Synthesis (19 papers)Advanced Adaptive Filtering Techniques (6 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Runsheng Liu
46 papers receiving 483 citations
Peers
Comparison fields: 5 of 85
- Signal Processing 268
- Artificial Intelligence 198
- Electrical and Electronic Engineering 75
- Computational Mechanics 71
- Cognitive Neuroscience 65
Countries citing papers authored by Runsheng Liu
This map shows the geographic impact of Runsheng Liu'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 Runsheng Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Runsheng Liu more than expected).
Fields of papers citing papers by Runsheng Liu
This network shows the impact of papers produced by Runsheng Liu. 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 Runsheng Liu. The network helps show where Runsheng Liu may publish in the future.
Co-authorship network of co-authors of Runsheng Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Runsheng Liu. A scholar is included among the top collaborators of Runsheng Liu 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 Runsheng Liu. Runsheng Liu 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 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 9 | |
| 7 | L p -Norm Constrained Coding With Frank-Wolfe Network. | 1 |
| 8 | 0 | |
| 9 | 64 | |
| 10 | Phone-based pronunciation quality assessment algorithm | 3 |
| 11 | 1 | |
| 12 | Multi-Pass Decoding Algorithm Based on a Speech Recognition Chip | 4 |
| 13 | 3 | |
| 14 | 2 | |
| 15 | 2 | |
| 16 | 1 | |
| 17 | 1 | |
| 18 | 33 | |
| 19 | High performance digit mandarin speech recognition | 1 |
| 20 | Use tone detection to improve performance of mandarin digit speech recognition | 1 |
About Runsheng Liu
Runsheng Liu is a scholar working on Signal Processing, Artificial Intelligence and Hardware and Architecture, having authored 50 papers that have together received 519 indexed citations. Recurring topics across this work include Speech and Audio Processing (23 papers), Speech Recognition and Synthesis (19 papers) and Advanced Adaptive Filtering Techniques (6 papers). The work is most often cited by research in Signal Processing (268 citations), Artificial Intelligence (198 citations) and Management of Technology and Innovation (31 citations). Runsheng Liu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yi Jiang, DeLiang Wang, Zhenming Feng, Yi Jiang, Jia Liu, Min Chu, Yining Chen, Eric Chang, Dong Wang and Jun Qi. Their work appears in journals such as Nano Energy, IEEE Transactions on Circuits and Systems for Video Technology and Scientometrics.
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.