Tim Schlippe
- Artificial Intelligence top 5%
- Natural Language Processing Techniques 26
- Speech Recognition and Synthesis 17
- Speech and dialogue systems 11
- Topic Modeling 11
- Text Readability and Simplification 4
- Signal Processing top 5%
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education 3
- Language and Linguistics top 10%
- Lexicography and Language Studies 5
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- Mathematics, Computing, and Information Processing 2
Tim Schlippe
39 papers receiving 460 citations
Peers
Comparison fields: 5 of 57
- Artificial Intelligence 435
- Signal Processing 124
- Health Informatics 14
- Language and Linguistics 55
- Experimental and Cognitive Psychology 55
Countries citing papers authored by Tim Schlippe
This map shows the geographic impact of Tim Schlippe'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 Tim Schlippe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Schlippe more than expected).
Fields of papers citing papers by Tim Schlippe
This network shows the impact of papers produced by Tim Schlippe. 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 Tim Schlippe. The network helps show where Tim Schlippe may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tim Schlippe, 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 | 1 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 8 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 4 | |
| 7 | 2023 | 5 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 1 | |
| 10 | NLP for Student and Teacher: Concept for an AI based Information Literacy Tutoring System. | 2020 | 3 |
| 11 | 2020 | 7 | |
| 12 | Automatic Detection of Anglicisms for the Pronunciation Dictionary Generation: A Case Study on our German IT Corpus | 2014 | 3 |
| 13 | Combining Grapheme-to-Phoneme Converter Outputs for Enhanced Pronunciation Generation in Low-Resource Scenarios | 2014 | 7 |
| 14 | Features for Factored Language Models for Code-Switching Speech | 2014 | 20 |
| 15 | GlobalPhone: Pronunciation Dictionaries in 20 Languages | 2014 | 8 |
| 16 | 2014 | 1 | |
| 17 | 2013 | 52 | |
| 18 | 2012 | 12 | |
| 19 | Hausa large vocabulary continuous speech recognition. | 2012 | 10 |
| 20 | 2008 | 5 |
About Tim Schlippe
Tim Schlippe is a scholar working on Health Informatics, Artificial Intelligence, Language and Linguistics, Human-Computer Interaction and Signal Processing, having authored 41 papers that have together received 516 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (26 papers), Speech Recognition and Synthesis (17 papers), Speech and dialogue systems (11 papers), Topic Modeling (11 papers), Lexicography and Language Studies (5 papers), Text Readability and Simplification (4 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Mathematics, Computing, and Information Processing (2 papers). The work is most often cited by research in Artificial Intelligence (435 citations), Signal Processing (124 citations), Health Informatics (14 citations), Language and Linguistics (55 citations) and Experimental and Cognitive Psychology (55 citations). Tim Schlippe has collaborated with scholars based in Germany, Qatar and United States. Frequent co-authors include Tanja Schultz, Ngoc Thang Vu, Haizhou Li, Dominic Telaar, Stephan Vogel, Heike Adel, Dau-Cheng Lyu, Jochen Weiner, Eng Siong Chng and Matthias Wölfel. Their work appears in journals such as Speech Communication, Language Resources and Evaluation, Big Data and Cognitive Computing, Applied Sciences 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.