Barry Vercoe

1.3k citations
29 papers · 658 · h-index 14

Impact in

Papers in

Barry Vercoe

26 papers receiving 515 citations

Peers

Barry Vercoe
Comparison fields: 5 of 46
  • Signal Processing 562
  • Computer Vision and Pattern Recognition 517
  • Cognitive Neuroscience 203
  • Music 30
  • Artificial Intelligence 78
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Citations per field
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Citations per year

Countries citing papers authored by Barry Vercoe

Since Specialization
Citations

This map shows the geographic impact of Barry Vercoe'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 Barry Vercoe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Barry Vercoe more than expected).

Fields of papers citing papers by Barry Vercoe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Barry Vercoe. 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 Barry Vercoe. The network helps show where Barry Vercoe may publish in the future.

Co-authors

The 14 scholars most cited alongside Barry Vercoe, 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 Barry Vercoe Line = papers co-authored together Barry Vercoe links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Folk Music Classification Using Hidden Markov Models
200191
2
The Synthetic Performer in The Context of Live Performance
198486
3
Music-listening systems
200081
4 199877
5
Synthetic Rehearsal: Training the Synthetic Performer
198543
6 200337
7 200031
8 200029
9
A Manual for the Audio Processing System and Supporting Programs with Tutorials
200126
10 200123
11
Music Content Analysis through Models of Audition
199823
12 200521
13
Real-time CSound: Software Synthesis with Sensing and Control
199019
14 200716
15
A Wavelet Based Sinusoid Model of Sound for Auditory Signal Separation
199110
16 20038
17
Connection Machine Tracking of Polyphonic Audio.
19886
18 19926
19
A Perceptual Representation of Sound for Auditory Signal Separation
19925
20 20035

About Barry Vercoe

Barry Vercoe is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Cognitive Neuroscience, Music and Artificial Intelligence, having authored 29 papers that have together received 658 indexed citations. Recurring topics across this work include Music Technology and Sound Studies (22 papers), Music and Audio Processing (21 papers), Speech and Audio Processing (14 papers), Neuroscience and Music Perception (4 papers), Image and Signal Denoising Methods (1 paper), Embedded Systems Design Techniques (1 paper), Advanced Text Analysis Techniques (1 paper) and Diverse Musicological Studies (1 paper). The work is most often cited by research in Signal Processing (562 citations), Computer Vision and Pattern Recognition (517 citations), Cognitive Neuroscience (203 citations), Music (30 citations) and Artificial Intelligence (78 citations). Barry Vercoe has collaborated with scholars based in United States. Frequent co-authors include Wei Chai, Eric D. Scheirer, William G. Gardner, Miller Puckette, Daniel P. W. Ellis, Ricardo Garcı́a, Youngmoo E. Kim, Keith D. Martin, David R. S. Cumming and Deb Roy. Their work appears in journals such as The Journal of the Acoustical Society of America, Proceedings of the IEEE, Computer Music Journal, BT Technology Journal and Perspectives of New Music.

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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