Timothy J. Hazen
- Signal Processing top 0.5%
- Music and Audio Processing 32
- Speech and Audio Processing 27
- Artificial Intelligence top 0.5%
- Speech Recognition and Synthesis 45
- Speech and dialogue systems 26
- Natural Language Processing Techniques 25
- Topic Modeling 17
- Text and Document Classification Technologies 4
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- Face recognition and analysis 3
- Human-Computer Interaction top 10%
- Co-authors
- James GlassStephanie SeneffVictor W. ZueJoseph PolifroniWade ShenChristopher WhiteJi MingAlex Park
- Journals
- The Journal of the Acoustical Society of America (1 paper)IEEE Signal Processing Magazine (1 paper)IEEE Transactions on Audio Speech and Language Processing (4 papers)
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Timothy J. Hazen
70 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 81
- Signal Processing 1.3k
- Artificial Intelligence 2.0k
- Computer Vision and Pattern Recognition 312
- Human-Computer Interaction 48
- Experimental and Cognitive Psychology 88
Countries citing papers authored by Timothy J. Hazen
This map shows the geographic impact of Timothy J. Hazen'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 Timothy J. Hazen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Timothy J. Hazen more than expected).
Fields of papers citing papers by Timothy J. Hazen
This network shows the impact of papers produced by Timothy J. Hazen. 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 Timothy J. Hazen. The network helps show where Timothy J. Hazen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Timothy J. Hazen, 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 | 2024 | 0 | |
| 2 | 2022 | 2 | |
| 3 | Robust Natural Language Inference Models with Example Forgetting. | 2019 | 7 |
| 4 | 2019 | 6 | |
| 5 | 2015 | 1 | |
| 6 | 2012 | 8 | |
| 7 | 2012 | 3 | |
| 8 | 2008 | 14 | |
| 9 | 2007 | 114 | |
| 10 | 2006 | 7 | |
| 11 | 2006 | 65 | |
| 12 | 2004 | 67 | |
| 13 | Rapid Speaker Adaptation With Speaker Clustering | 2002 | 6 |
| 14 | 2002 | 99 | |
| 15 | 2001 | 11 | |
| 16 | 2000 | 31 | |
| 17 | 1998 | 24 | |
| 18 | 1997 | 32 | |
| 19 | 1994 | 25 | |
| 20 | 1993 | 32 |
About Timothy J. Hazen
Timothy J. Hazen is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 72 papers that have together received 2.4k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (45 papers), Music and Audio Processing (32 papers), Speech and Audio Processing (27 papers), Speech and dialogue systems (26 papers), Natural Language Processing Techniques (25 papers), Topic Modeling (17 papers), Text and Document Classification Technologies (4 papers) and Face recognition and analysis (3 papers). The work is most often cited by research in Signal Processing (1.3k citations), Artificial Intelligence (2.0k citations) and Computer Vision and Pattern Recognition (312 citations). Timothy J. Hazen has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include James Glass, Stephanie Seneff, Victor W. Zue, Joseph Polifroni, Wade Shen, Christopher White, Ji Ming, Alex Park, Lee Hetherington and Douglas A. Reynolds. Their work appears in journals such as The Journal of the Acoustical Society of America, IEEE Signal Processing Magazine and IEEE Transactions on Audio Speech and Language Processing.
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.