Brian Whitman
- Signal Processing top 0.5%
- Music and Audio Processing 19
- Speech and Audio Processing 7
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- Music Technology and Sound Studies 14
- Music top 2%
- Diverse Musicological Studies 5
- Artificial Intelligence top 5%
- Speech Recognition and Synthesis 3
- Advanced Text Analysis Techniques 2
- Natural Language Processing Techniques 2
- Cognitive Neuroscience top 10%
- Neuroscience and Music Perception 2
- Co-authors
- Daniel P. W. EllisPaul LamereThierry Bertin-MahieuxAdam BerenzweigSteve LawrenceBeth LoganParis SmaragdisGary William Flake
- Journals
- Computer Music Journal (1 paper)JACC. Cardiovascular imaging (1 paper)ACM Transactions on Multimedia Computing Communications and Applications (1 paper)
- Partner nations
- United StatesFinlandCanada
In The Last Decade
Brian Whitman
23 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Signal Processing 879
- Computer Vision and Pattern Recognition 726
- Music 80
- Artificial Intelligence 353
- Cognitive Neuroscience 141
Countries citing papers authored by Brian Whitman
This map shows the geographic impact of Brian Whitman'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 Brian Whitman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian Whitman more than expected).
Fields of papers citing papers by Brian Whitman
This network shows the impact of papers produced by Brian Whitman. 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 Brian Whitman. The network helps show where Brian Whitman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Brian Whitman, 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 | 2016 | 36 | |
| 2 | 2014 | 19 | |
| 3 | 2013 | 1 | |
| 4 | The Million Song Datasetbreakdown → | 2011 | 445 |
| 5 | 2010 | 3 | |
| 6 | 2010 | 7 | |
| 7 | 2006 | 3 | |
| 8 | 2005 | 2 | |
| 9 | 2004 | 189 | |
| 10 | 2004 | 6 | |
| 11 | 2004 | 32 | |
| 12 | 2004 | 49 | |
| 13 | 2003 | 8 | |
| 14 | 2003 | 54 | |
| 15 | Inferring Descriptions and Similarity for Music from Community Metadata | 2002 | 79 |
| 16 | 2002 | 105 | |
| 17 | 2002 | 2 | |
| 18 | 2002 | 65 | |
| 19 | 2001 | 9 | |
| 20 | 2000 | 5 |
About Brian Whitman
Brian Whitman is a scholar working on Signal Processing, Music, Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience, having authored 23 papers that have together received 1.2k indexed citations. Recurring topics across this work include Music and Audio Processing (19 papers), Music Technology and Sound Studies (14 papers), Speech and Audio Processing (7 papers), Diverse Musicological Studies (5 papers), Speech Recognition and Synthesis (3 papers), Advanced Text Analysis Techniques (2 papers), Neuroscience and Music Perception (2 papers) and Natural Language Processing Techniques (2 papers). The work is most often cited by research in Signal Processing (879 citations), Computer Vision and Pattern Recognition (726 citations), Music (80 citations), Artificial Intelligence (353 citations) and Cognitive Neuroscience (141 citations). Brian Whitman has collaborated with scholars based in United States, Finland and Canada. Frequent co-authors include Daniel P. W. Ellis, Paul Lamere, Thierry Bertin-Mahieux, Adam Berenzweig, Steve Lawrence, Beth Logan, Paris Smaragdis, Gary William Flake, Sandra Lawrence and Ryan Rifkin. Their work appears in journals such as Computer Music Journal, JACC. Cardiovascular imaging, ACM Transactions on Multimedia Computing Communications and Applications, Zenodo (CERN European Organization for Nuclear Research) and Project Muse (Johns Hopkins University).
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.