Steve Lowe
Impact in
- Signal Processing top 10%
- Music and Audio Processing
- Speech and Audio Processing
- Artificial Intelligence top 5%
- Speech Recognition and Synthesis
- Natural Language Processing Techniques
- Topic Modeling
- Advanced Text Analysis Techniques
- Speech and dialogue systems
- Text and Document Classification Technologies
Papers in
-
- Speech Recognition and Synthesis 9
- Natural Language Processing Techniques 6
- Topic Modeling 3
- Speech and dialogue systems 2
-
- Music and Audio Processing 4
- Speech and Audio Processing 2
- Co-authors
- Paul van Mulbregt (3 shared papers)Man-Hung Siu (4 shared papers)H. Gish (4 shared papers)Larry Gillick (3 shared papers)Shosuke Ito (2 shared papers)Michael Newman (1 shared paper)Barbara Peskin (2 shared papers)Timothy J. Hazen (1 shared paper)
- Partner nations
- United States
In The Last Decade
Steve Lowe
11 papers receiving 204 citations
Peers
Comparison fields: 5 of 33
- Signal Processing 94
- Artificial Intelligence 217
- Computer Vision and Pattern Recognition 36
- Computational Mathematics 1
- Information Systems 31
Countries citing papers authored by Steve Lowe
This map shows the geographic impact of Steve Lowe'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 Steve Lowe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steve Lowe more than expected).
Fields of papers citing papers by Steve Lowe
This network shows the impact of papers produced by Steve Lowe. 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 Steve Lowe. The network helps show where Steve Lowe may publish in the future.
Co-authors
The 13 scholars most cited alongside Steve Lowe, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2002 | 68 | |
| 2 | 1998 | 53 | |
| 3 | 2013 | 50 | |
| 4 | 2002 | 16 | |
| 5 | 2011 | 14 | |
| 6 | 2011 | 10 | |
| 7 | 2002 | 9 | |
| 8 | 1994 | 7 | |
| 9 | 2002 | 7 | |
| 10 | 2012 | 2 | |
| 11 | 2024 | 1 |
About Steve Lowe
Steve Lowe is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Endocrinology, Diabetes and Metabolism and Biophysics, having authored 11 papers that have together received 237 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (9 papers), Natural Language Processing Techniques (6 papers), Music and Audio Processing (4 papers), Topic Modeling (3 papers), Speech and Audio Processing (2 papers), Speech and dialogue systems (2 papers), Spectroscopy Techniques in Biomedical and Chemical Research (1 paper) and Diabetes Management and Research (1 paper). The work is most often cited by research in Signal Processing (94 citations), Artificial Intelligence (217 citations), Computer Vision and Pattern Recognition (36 citations), Computational Mathematics (1 citation) and Information Systems (31 citations). Steve Lowe has collaborated with scholars based in United States. Frequent co-authors include Paul van Mulbregt, Man-Hung Siu, H. Gish, Larry Gillick, Shosuke Ito, Michael Newman, Barbara Peskin, Timothy J. Hazen, Mark A. Mandel and Guoming Gao. Their work appears in journals such as IEEE Sensors Journal and Computer Speech & Language.
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.