Douglas Eck
Impact in
- Signal Processing top 0.2%
- Music and Audio Processing
- Speech and Audio Processing
- Time Series Analysis and Forecasting
-
- Music Technology and Sound Studies
Papers in
-
- Music and Audio Processing 49
- Speech and Audio Processing 16
-
- Music Technology and Sound Studies 43
- Co-authors
- Jürgen Schmidhuber (11 shared papers)Felix A. Gers (6 shared papers)Philippe Hamel (4 shared papers)Paul Lamere (5 shared papers)Thierry Bertin-Mahieux (6 shared papers)Norman Casagrande (4 shared papers)James Bergstra (3 shared papers)Balázs Kégl (4 shared papers)
- Journals
- Journal of New Music Research (2 papers)Artificial Intelligence (1 paper)Machine Learning (1 paper)Psychological Research (1 paper)Music Perception An Interdisciplinary Journal (1 paper)
- Partner nations
- CanadaUnited StatesSwitzerland
In The Last Decade
Douglas Eck
71 papers receiving 2.7k citations
Douglas Eck's Hit Papers
Peers
Comparison fields: 5 of 134
- Signal Processing 1.6k
- Computer Vision and Pattern Recognition 1.5k
- Music 110
- Cognitive Neuroscience 581
- Artificial Intelligence 951
Countries citing papers authored by Douglas Eck
This map shows the geographic impact of Douglas Eck'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 Douglas Eck with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Douglas Eck more than expected).
Fields of papers citing papers by Douglas Eck
This network shows the impact of papers produced by Douglas Eck. 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 Douglas Eck. The network helps show where Douglas Eck may publish in the future.
Co-authors
The 25 scholars most cited alongside Douglas Eck, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2001 | 250 | |
| 2 | 2006 | 220 | |
| 3 | 2002 | 197 | |
| 4 | Deduplicating Training Data Makes Language Models Better Hit paper breakdown → | 2022 | 188 |
| 5 | 2010 | 183 | |
| 6 | Music Transformer: Generating Music with Long-Term Structure | 2019 | 165 |
| 7 | 2003 | 154 | |
| 8 | 2002 | 133 | |
| 9 | Automatic Generation of Social Tags for Music Recommendation | 2007 | 126 |
| 10 | 2008 | 85 | |
| 11 | 2003 | 83 | |
| 12 | 2011 | 69 | |
| 13 | 2004 | 69 | |
| 14 | 2002 | 56 | |
| 15 | 2002 | 52 | |
| 16 | 2011 | 47 | |
| 17 | 2010 | 44 | |
| 18 | 2009 | 42 | |
| 19 | 2006 | 40 | |
| 20 | 2005 | 40 |
About Douglas Eck
Douglas Eck is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Artificial Intelligence and Music, having authored 72 papers that have together received 2.9k indexed citations. Recurring topics across this work include Music and Audio Processing (49 papers), Music Technology and Sound Studies (43 papers), Neuroscience and Music Perception (19 papers), Speech and Audio Processing (16 papers), Topic Modeling (8 papers), Neural Networks and Applications (6 papers), Natural Language Processing Techniques (5 papers) and Neural dynamics and brain function (5 papers). The work is most often cited by research in Signal Processing (1.6k citations), Computer Vision and Pattern Recognition (1.5k citations), Music (110 citations), Cognitive Neuroscience (581 citations) and Artificial Intelligence (951 citations). Douglas Eck has collaborated with scholars based in Canada, United States and Switzerland. Frequent co-authors include Jürgen Schmidhuber, Felix A. Gers, Philippe Hamel, Paul Lamere, Thierry Bertin-Mahieux, Norman Casagrande, James Bergstra, Balázs Kégl, Dumitru Erhan and Chris Callison-Burch. Their work appears in journals such as Journal of New Music Research, Artificial Intelligence, Machine Learning, Psychological Research and Music Perception An Interdisciplinary Journal.
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.