Jeff Bilmes
Impact in
- Signal Processing top 5%
- Speech and Audio Processing
- Music and Audio Processing
- Artificial Intelligence top 5%
- Speech Recognition and Synthesis
- Natural Language Processing Techniques
- Topic Modeling
- Speech and dialogue systems
- Machine Learning and Algorithms
Papers in
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- Speech Recognition and Synthesis 6
- Speech and dialogue systems 3
- Natural Language Processing Techniques 2
- Neural Networks and Applications 2
- Algorithms and Data Compression 2
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- Speech and Audio Processing 2
- Music and Audio Processing 2
- Co-authors
- Hui Lin (2 shared papers)Karen Livescu (1 shared paper)James Glass (1 shared paper)Katrin Kirchhoff (1 shared paper)Dimitra Vergyri (1 shared paper)Kevin Duh (1 shared paper)Andreas Stolcke (1 shared paper)Danny Wyatt (1 shared paper)
- Journals
- Computer Speech & Language (1 paper)IEEE Signal Processing Magazine (1 paper)Edinburgh Research Explorer (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Jeff Bilmes
9 papers receiving 265 citations
Peers
Comparison fields: 5 of 53
- Signal Processing 110
- Artificial Intelligence 242
- Experimental and Cognitive Psychology 39
- Computer Vision and Pattern Recognition 36
- Applied Psychology 6
Countries citing papers authored by Jeff Bilmes
This map shows the geographic impact of Jeff Bilmes'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 Jeff Bilmes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeff Bilmes more than expected).
Fields of papers citing papers by Jeff Bilmes
This network shows the impact of papers produced by Jeff Bilmes. 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 Jeff Bilmes. The network helps show where Jeff Bilmes may publish in the future.
Co-authors
The 12 scholars most cited alongside Jeff Bilmes, 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 | 2005 | 80 | |
| 2 | 2003 | 50 | |
| 3 | 2009 | 49 | |
| 4 | 2007 | 41 | |
| 5 | 2005 | 31 | |
| 6 | 2010 | 25 | |
| 7 | 2009 | 14 | |
| 8 | 2009 | 11 | |
| 9 | 2010 | 2 |
About Jeff Bilmes
Jeff Bilmes is a scholar working on Artificial Intelligence, Signal Processing, Computer Networks and Communications, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 9 papers that have together received 303 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (6 papers), Speech and dialogue systems (3 papers), Speech and Audio Processing (2 papers), Natural Language Processing Techniques (2 papers), Neural Networks and Applications (2 papers), Music and Audio Processing (2 papers), Algorithms and Data Compression (2 papers) and Error Correcting Code Techniques (1 paper). The work is most often cited by research in Signal Processing (110 citations), Artificial Intelligence (242 citations), Experimental and Cognitive Psychology (39 citations), Computer Vision and Pattern Recognition (36 citations) and Applied Psychology (6 citations). Jeff Bilmes has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Hui Lin, Karen Livescu, James Glass, Katrin Kirchhoff, Dimitra Vergyri, Kevin Duh, Andreas Stolcke, Danny Wyatt, Tanzeem Choudhury and Simon King. Their work appears in journals such as Computer Speech & Language, IEEE Signal Processing Magazine and Edinburgh Research Explorer.
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.