Cyril Joder
Impact in
- Signal Processing top 5%
- Music and Audio Processing
- Speech and Audio Processing
- Blind Source Separation Techniques
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- Music Technology and Sound Studies
Papers in
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- Speech and Audio Processing 10
- Music and Audio Processing 9
- Blind Source Separation Techniques 2
- Time Series Analysis and Forecasting 1
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- Music Technology and Sound Studies 5
- Co-authors
- Slim Essid (4 shared papers)Gaël Richard (3 shared papers)Björn W. Schuller (7 shared papers)Felix Weninger (3 shared papers)Gaël Richard (1 shared paper)Florian Eyben (1 shared paper)Martin Wöllmer (1 shared paper)
- Journals
- IEEE Transactions on Audio Speech and Language Processing (3 papers)Lecture notes in computer science (1 paper)OPUS (Augsburg University) (1 paper)mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (4 papers)HAL (Le Centre pour la Communication Scientifique Directe) (1 paper)
In The Last Decade
Cyril Joder
11 papers receiving 238 citations
Peers
Comparison fields: 5 of 27
- Signal Processing 238
- Computer Vision and Pattern Recognition 120
- Developmental Biology 7
- Music 10
- Computational Mechanics 37
Countries citing papers authored by Cyril Joder
This map shows the geographic impact of Cyril Joder'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 Cyril Joder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cyril Joder more than expected).
Fields of papers citing papers by Cyril Joder
This network shows the impact of papers produced by Cyril Joder. 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 Cyril Joder. The network helps show where Cyril Joder may publish in the future.
Co-authors
The 7 scholars most cited alongside Cyril Joder, 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 | 2009 | 86 | |
| 2 | 2012 | 43 | |
| 3 | 2011 | 42 | |
| 4 | Exploring Nonnegative Matrix Factorization for Audio Classification: Application to Speaker Recognition | 2012 | 15 |
| 5 | 2013 | 15 | |
| 6 | 2013 | 13 | |
| 7 | 2012 | 11 | |
| 8 | The TUM Cumulative DTW Approach for the Mediaeval 2012 Spoken Web Search Task | 2012 | 7 |
| 9 | 2013 | 7 | |
| 10 | 2010 | 6 | |
| 11 | 2013 | 6 |
About Cyril Joder
Cyril Joder is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mechanics and Infectious Diseases, having authored 11 papers that have together received 251 indexed citations. Recurring topics across this work include Speech and Audio Processing (10 papers), Music and Audio Processing (9 papers), Music Technology and Sound Studies (5 papers), Blind Source Separation Techniques (2 papers), Speech Recognition and Synthesis (2 papers), Advanced Adaptive Filtering Techniques (1 paper), Time Series Analysis and Forecasting (1 paper) and Advanced Text Analysis Techniques (1 paper). The work is most often cited by research in Signal Processing (238 citations), Computer Vision and Pattern Recognition (120 citations), Developmental Biology (7 citations), Music (10 citations) and Computational Mechanics (37 citations). Cyril Joder has collaborated with scholars based in Germany and France. Frequent co-authors include Slim Essid, Gaël Richard, Björn W. Schuller, Felix Weninger, Gaël Richard, Florian Eyben and Martin Wöllmer. Their work appears in journals such as IEEE Transactions on Audio Speech and Language Processing, Lecture notes in computer science, OPUS (Augsburg University), mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) and HAL (Le Centre pour la Communication Scientifique Directe).
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.