Tim Polzehl

1.0k citations
50 papers · 568 · h-index 14

Impact in

Papers in

    • Speech Recognition and Synthesis 19
    • Speech and dialogue systems 11
    • Topic Modeling 7
    • Natural Language Processing Techniques 5
    • Speech and Audio Processing 12
    • Music and Audio Processing 8

Tim Polzehl

48 papers receiving 516 citations

Peers

Tim Polzehl
Comparison fields: 5 of 64
  • Signal Processing 214
  • Experimental and Cognitive Psychology 255
  • Artificial Intelligence 293
  • Pharmacy 34
  • Computer Science Applications 31
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Citations per field
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Citations per year

Countries citing papers authored by Tim Polzehl

Since Specialization
Citations

This map shows the geographic impact of Tim Polzehl'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 Polzehl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Polzehl more than expected).

Fields of papers citing papers by Tim Polzehl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tim Polzehl. 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 Polzehl. The network helps show where Tim Polzehl may publish in the future.

Co-authors

The 25 scholars most cited alongside Tim Polzehl, 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 Polzehl Line = papers co-authored together Tim Polzehl links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201172
2 201060
3 200937
4 200930
5 201027
6 201525
7 202224
8 200923
9 200921
10 201019
11 201218
12 200913
13 202013
14 201413
15 201011
16 201011
17 200911
18 201210
19
Reliability of Human Evaluation for Text Summarization: Lessons Learned and Challenges Ahead
202110
20 20229

About Tim Polzehl

Tim Polzehl is a scholar working on Artificial Intelligence, Signal Processing, Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition and Computer Science Applications, having authored 50 papers that have together received 568 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (19 papers), Speech and Audio Processing (12 papers), Speech and dialogue systems (11 papers), Emotion and Mood Recognition (9 papers), Music and Audio Processing (8 papers), Topic Modeling (7 papers), Mobile Crowdsensing and Crowdsourcing (6 papers) and Natural Language Processing Techniques (5 papers). The work is most often cited by research in Signal Processing (214 citations), Experimental and Cognitive Psychology (255 citations), Artificial Intelligence (293 citations), Pharmacy (34 citations) and Computer Science Applications (31 citations). Tim Polzehl has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Florian Metze, Sebastian Möller, Michael Wagner, Alexander Schmitt, Hamed Ketabdar, Felix Burkhardt, Joachim Stegmann, Babak Naderi, Tiago H. Falk and Richard Huber. Their work appears in journals such as Language Resources and Evaluation, Speech Communication, Lecture notes in computer science, arXiv (Cornell University) and CERN Document Server (European Organization for Nuclear Research).

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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