Daniel Wolff
Impact in
- Developmental Biology top 1%
- Animal Vocal Communication and Behavior
- Signal Processing top 5%
- Music and Audio Processing
- Speech and Audio Processing
Papers in
-
- Music and Audio Processing 14
- Speech and Audio Processing 4
-
- Music Technology and Sound Studies 12
- Co-authors
- Rolf Bardeli (1 shared paper)Markus Koch (1 shared paper)Frank Kurth (1 shared paper)Karl‐Heinz Frommolt (1 shared paper)Tillman Weyde (13 shared papers)Nicolas Gold (3 shared papers)Samer Abdallah (3 shared papers)Emmanouil Benetos (4 shared papers)
- Journals
- IEEE Signal Processing Letters (1 paper)Pattern Recognition Letters (1 paper)Journal on Computing and Cultural Heritage (1 paper)Information Retrieval (1 paper)Journal of Web Semantics (1 paper)
- Partner nations
- United KingdomGermanyFrance
In The Last Decade
Daniel Wolff
16 papers receiving 288 citations
Peers
Comparison fields: 5 of 48
- Developmental Biology 196
- Signal Processing 170
- Music 23
- Ecology 131
- Ecological Modeling 19
Countries citing papers authored by Daniel Wolff
This map shows the geographic impact of Daniel Wolff'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 Daniel Wolff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Wolff more than expected).
Fields of papers citing papers by Daniel Wolff
This network shows the impact of papers produced by Daniel Wolff. 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 Daniel Wolff. The network helps show where Daniel Wolff may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Wolff, 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 | 237 | |
| 2 | 2017 | 13 | |
| 3 | 2013 | 13 | |
| 4 | 2011 | 10 | |
| 5 | Big Chord Data Extraction and Mining | 2014 | 8 |
| 6 | 2014 | 7 | |
| 7 | 2012 | 4 | |
| 8 | 2022 | 2 | |
| 9 | 2021 | 2 | |
| 10 | Creating audio based experiments as social Web games with the CASimIR framework | 2014 | 2 |
| 11 | 2016 | 2 | |
| 12 | 2012 | 2 | |
| 13 | Feature Preprocessing with Restricted Boltzmann Machines for Music Similarity Learning | 2014 | 1 |
| 14 | 2016 | 1 | |
| 15 | 2014 | 1 | |
| 16 | 2015 | 1 |
About Daniel Wolff
Daniel Wolff is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Music, Cognitive Neuroscience and Artificial Intelligence, having authored 16 papers that have together received 306 indexed citations. Recurring topics across this work include Music and Audio Processing (14 papers), Music Technology and Sound Studies (12 papers), Speech and Audio Processing (4 papers), Diverse Musicological Studies (4 papers), Neuroscience and Music Perception (3 papers), Animal Vocal Communication and Behavior (1 paper), Data Stream Mining Techniques (1 paper) and Acoustic Wave Phenomena Research (1 paper). The work is most often cited by research in Developmental Biology (196 citations), Signal Processing (170 citations), Music (23 citations), Ecology (131 citations) and Ecological Modeling (19 citations). Daniel Wolff has collaborated with scholars based in United Kingdom, Germany and France. Frequent co-authors include Rolf Bardeli, Markus Koch, Frank Kurth, Karl‐Heinz Frommolt, Tillman Weyde, Nicolas Gold, Samer Abdallah, Emmanouil Benetos, Mathieu Barthet and Mark D. Plumbley. Their work appears in journals such as IEEE Signal Processing Letters, Pattern Recognition Letters, Journal on Computing and Cultural Heritage, Information Retrieval and Journal of Web Semantics.
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.