Sebastian Stüker
- Artificial Intelligence top 1%
- Signal Processing top 2%
- Computer Vision and Pattern Recognition top 10%
- Language and Linguistics top 10%
- Experimental and Cognitive Psychology
- Co-authors
- Tanja SchultzAlex WaibelMarcello FedericoJan NiehuesLuisa BentivogliFlorian MetzeMarkus MüllerChristian Fügen
- Topics
- Natural Language Processing Techniques (50 papers)Speech Recognition and Synthesis (43 papers)Speech and dialogue systems (27 papers)
- Journals
- SHILAP Revista de lepidopterologíaLanguage Resources and EvaluationIEEE Potentials
- Partner nations
- GermanyUnited StatesItaly
In The Last Decade
Sebastian Stüker
68 papers receiving 760 citations
Peers
Comparison fields: 5 of 39
- Artificial Intelligence 885
- Signal Processing 274
- Computer Vision and Pattern Recognition 121
- Language and Linguistics 43
- Experimental and Cognitive Psychology 39
Countries citing papers authored by Sebastian Stüker
This map shows the geographic impact of Sebastian Stüker'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 Sebastian Stüker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sebastian Stüker more than expected).
Fields of papers citing papers by Sebastian Stüker
This network shows the impact of papers produced by Sebastian Stüker. 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 Sebastian Stüker. The network helps show where Sebastian Stüker may publish in the future.
Co-authorship network of co-authors of Sebastian Stüker
This figure shows the co-authorship network connecting the top 25 collaborators of Sebastian Stüker. A scholar is included among the top collaborators of Sebastian Stüker 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 Sebastian Stüker. Sebastian Stüker is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 0 | |
| 3 | Removing European Language Barriers with Innovative Machine Translation Technology | 6 |
| 4 | 47 | |
| 5 | 12 | |
| 6 | 24 | |
| 7 | 6 | |
| 8 | 4 | |
| 9 | 1 | |
| 10 | 15 | |
| 11 | 3 | |
| 12 | 3 | |
| 13 | 12 | |
| 14 | 6 | |
| 15 | 47 | |
| 16 | 8 | |
| 17 | 9 | |
| 18 | 13 | |
| 19 | 13 | |
| 20 | 52 |
About Sebastian Stüker
Sebastian Stüker is a scholar working on Artificial Intelligence, Signal Processing and Language and Linguistics, having authored 69 papers that have together received 931 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (50 papers), Speech Recognition and Synthesis (43 papers) and Speech and dialogue systems (27 papers). The work is most often cited by research in Artificial Intelligence (885 citations), Signal Processing (274 citations) and Computer Vision and Pattern Recognition (121 citations). Sebastian Stüker has collaborated with scholars based in Germany, United States and Italy. Frequent co-authors include Tanja Schultz, Alex Waibel, Marcello Federico, Jan Niehues, Luisa Bentivogli, Florian Metze, Markus Müller, Christian Fügen, Mauro Cettolo and Roldano Cattoni. Their work appears in journals such as SHILAP Revista de lepidopterología, Language Resources and Evaluation and IEEE Potentials.
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.