Ute Essen
Impact in
- Artificial Intelligence top 5%
- Natural Language Processing Techniques
- Topic Modeling
- Speech Recognition and Synthesis
- Speech and dialogue systems
- Algorithms and Data Compression
- Signal Processing top 5%
- Speech and Audio Processing
- Music and Audio Processing
Papers in
-
- Speech Recognition and Synthesis 8
- Natural Language Processing Techniques 7
- Topic Modeling 3
- Speech and dialogue systems 3
- AI-based Problem Solving and Planning 1
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- Speech and Audio Processing 1
- Time Series Analysis and Forecasting 1
- Co-authors
- Hermann Ney (11 shared papers)Reinhard Kneser (7 shared papers)Volker Steinbiss (6 shared papers)Reinhold Haeb‐Umbach (5 shared papers)Xavier L. Aubert (4 shared papers)Martin Oerder (4 shared papers)
In The Last Decade
Ute Essen
12 papers receiving 552 citations
Peers
Comparison fields: 5 of 52
- Artificial Intelligence 566
- Signal Processing 113
- Language and Linguistics 42
- Experimental and Cognitive Psychology 46
- Information Systems 59
Countries citing papers authored by Ute Essen
This map shows the geographic impact of Ute Essen'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 Ute Essen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ute Essen more than expected).
Fields of papers citing papers by Ute Essen
This network shows the impact of papers produced by Ute Essen. 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 Ute Essen. The network helps show where Ute Essen may publish in the future.
Co-authors
The 6 scholars most cited alongside Ute Essen, 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 | 1994 | 372 | |
| 2 | 1995 | 58 | |
| 3 | 1991 | 54 | |
| 4 | 1992 | 51 | |
| 5 | 1993 | 36 | |
| 6 | 1994 | 22 | |
| 7 | 1995 | 20 | |
| 8 | 1993 | 14 | |
| 9 | 1995 | 10 | |
| 10 | 1994 | 8 | |
| 11 | 1993 | 1 | |
| 12 | 1995 | 1 |
About Ute Essen
Ute Essen is a scholar working on Artificial Intelligence, Signal Processing, Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition and Insect Science, having authored 12 papers that have together received 647 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (8 papers), Natural Language Processing Techniques (7 papers), Topic Modeling (3 papers), Speech and dialogue systems (3 papers), Advanced Data Compression Techniques (1 paper), AI-based Problem Solving and Planning (1 paper), Speech and Audio Processing (1 paper) and Time Series Analysis and Forecasting (1 paper). The work is most often cited by research in Artificial Intelligence (566 citations), Signal Processing (113 citations), Language and Linguistics (42 citations), Experimental and Cognitive Psychology (46 citations) and Information Systems (59 citations). Ute Essen has collaborated with scholars based in Germany and Finland. Frequent co-authors include Hermann Ney, Reinhard Kneser, Volker Steinbiss, Reinhold Haeb‐Umbach, Xavier L. Aubert and Martin Oerder. Their work appears in journals such as Computer Speech & Language, Speech Communication, IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Pattern Recognition and Artificial Intelligence and RWTH Publications (RWTH Aachen).
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.