Brian Whitman

2.0k citations
23 papers · 1.2k · 1 hit paper · h-index 11

Impact in

Papers in

Brian Whitman

23 papers receiving 1.0k citations

Brian Whitman's Hit Papers

The Million Song Dataset 2011 · 444 citations
4440+5+10Years since publication100200300400

Peers

Brian Whitman
Comparison fields: 5 of 85
  • Signal Processing 877
  • Computer Vision and Pattern Recognition 723
  • Music 79
  • Artificial Intelligence 354
  • Cognitive Neuroscience 141
Replace Peter Knees with:
Peter Knees Austria
Thierry Bertin-Mahieux United States
Pedro Cano Spain
Paul Lamere United States
Julián Urbano Spain
Douglas Turnbull United States
Zongheng Yang United States
Artur d’Avila Garcez United Kingdom
Paul Vickers United Kingdom
Jean-Pierre Briot France
Brian Whitman relative to Peter Knees Austria Peter Knees's profile →
Citations per field
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Citations per year

Countries citing papers authored by Brian Whitman

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

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.

Border = papers with Brian Whitman Line = papers co-authored together Brian Whitman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The Million Song Dataset
Hit paper breakdown →
2011444
2 2004189
3 2002104
4
Inferring Descriptions and Similarity for Music from Community Metadata
200279
5 200265
6 200354
7 200253
8 200450
9 201638
10 200432
11 201420
12 200110
13 201110
14 20038
15 20107
16 20046
17 20005
18 20103
19 20063
20
MUSICALLY EXPRESSIVE SOUND TEXTURES FROM GENERALIZED AUDIO
20033

About Brian Whitman

Brian Whitman is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Artificial Intelligence, Music 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), Natural Language Processing Techniques (2 papers) and Neuroscience and Music Perception (2 papers). The work is most often cited by research in Signal Processing (877 citations), Computer Vision and Pattern Recognition (723 citations), Music (79 citations), Artificial Intelligence (354 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, Sandra Lawrence, Gary William Flake and Ryan Rifkin. Their work appears in journals such as ACM Transactions on Multimedia Computing Communications and Applications, Computer Music Journal, JACC. Cardiovascular imaging, Columbia Academic Commons (Columbia University) 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.

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