Tim Schlippe

1.1k citations
57 papers · 690 · h-index 15

Impact in

    • Artificial Intelligence in Healthcare and Education
    • Natural Language Processing Techniques
    • Speech Recognition and Synthesis
    • Topic Modeling
    • Speech and dialogue systems

Papers in

Tim Schlippe

51 papers receiving 627 citations

Peers

Tim Schlippe
Comparison fields: 5 of 68
  • Health Informatics 38
  • Artificial Intelligence 566
  • Signal Processing 134
  • Computer Science Applications 38
  • Language and Linguistics 63
Replace Hrafn Loftsson with:
Hrafn Loftsson Iceland
Sophie Rosset France
Pierre Lison Norway
Ryuichiro Higashinaka Japan
Janet Hitzeman United States
Aoife Cahill United States
Genta Indra Winata Hong Kong
Katrin Tomanek Germany
Grzegorz Chrupała Netherlands
Fadi Biadsy United States
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Citations per year

Countries citing papers authored by Tim Schlippe

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

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.

Border = papers with Tim Schlippe Line = papers co-authored together Tim Schlippe links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012105
2 201372
3 201357
4 201030
5 202329
6 202423
7 201023
8 201522
9
Features for Factored Language Models for Code-Switching Speech
201421
10 201221
11 202218
12 202318
13 201417
14 201017
15 200816
16 201213
17 201312
18 202112
19
Hausa large vocabulary continuous speech recognition.
201210
20 20249

About Tim Schlippe

Tim Schlippe is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Language and Linguistics, Information Systems and Computer Science Applications, having authored 57 papers that have together received 690 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (32 papers), Topic Modeling (20 papers), Speech Recognition and Synthesis (18 papers), Speech and dialogue systems (11 papers), Text Readability and Simplification (7 papers), Lexicography and Language Studies (5 papers), Online Learning and Analytics (4 papers) and Multimodal Machine Learning Applications (3 papers). The work is most often cited by research in Health Informatics (38 citations), Artificial Intelligence (566 citations), Signal Processing (134 citations), Computer Science Applications (38 citations) and Language and Linguistics (63 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, Kristina Schaaff, Dominic Telaar, Stephan Vogel, Heike Adel, Dau-Cheng Lyu, Jochen Weiner and Eng Siong Chng. Their work appears in journals such as Big Data and Cognitive Computing, Speech Communication, International Journal of Speech Technology, Language Resources and Evaluation 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.

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