Cory McKay

1.2k citations
33 papers · 859 · h-index 13

Impact in

    • Music and Audio Processing
    • Speech and Audio Processing
  • Music top 1%
    • Diverse Musicological Studies
    • Diverse Music Education Insights

Papers in

Cory McKay

33 papers receiving 769 citations

Peers

Cory McKay
Comparison fields: 5 of 48
  • Signal Processing 692
  • Music 112
  • Computer Vision and Pattern Recognition 655
  • Cognitive Neuroscience 269
  • Experimental and Cognitive Psychology 55
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Óscar Mayor Spain
Lars Frydén Sweden
Maarten Grachten Austria
Matthew E. P. Davies Portugal
Esteban Maestre Spain
Anja Volk Netherlands
Emilios Cambouropoulos Greece
Maximos A. Kaliakatsos-Papakostas Greece
André Holzapfel Sweden
Cyril Laurier Spain
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Citations per field
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Citations per year

Countries citing papers authored by Cory McKay

Since Specialization
Citations

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

Fields of papers citing papers by Cory McKay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside Cory McKay, 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 Cory McKay Line = papers co-authored together Cory McKay links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005174
2 2005136
3 2004126
4 200691
5
jSymbolic: A Feature Extractor for MIDI Files
200649
6 201040
7 200634
8 200827
9 200526
10 201024
11 200622
12
Overview of OMEN
200617
13
jMIR: Tools for Automatic Music Classification
200917
14 200511
15 201010
16 20098
17 20076
18 20186
19 20226
20 20055

About Cory McKay

Cory McKay is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Music, Cognitive Neuroscience and Artificial Intelligence, having authored 33 papers that have together received 859 indexed citations. Recurring topics across this work include Music and Audio Processing (30 papers), Music Technology and Sound Studies (27 papers), Diverse Musicological Studies (8 papers), Speech and Audio Processing (7 papers), Neuroscience and Music Perception (5 papers), Algorithms and Data Compression (3 papers), Time Series Analysis and Forecasting (3 papers) and Video Analysis and Summarization (3 papers). The work is most often cited by research in Signal Processing (692 citations), Music (112 citations), Computer Vision and Pattern Recognition (655 citations), Cognitive Neuroscience (269 citations) and Experimental and Cognitive Psychology (55 citations). Cory McKay has collaborated with scholars based in Canada, Spain and Germany. Frequent co-authors include Ichiro Fujinaga, Neil Middleton, Marcelo M. Wanderley, Bradley W. Vines, Philippe Depalle, Rebecca Fiebrink, John Burgoyne, Jordan B. L. Smith, Jessica Thompson and David Bainbridge. Their work appears in journals such as Journal of New Music Research, Digital Scholarship in the Humanities, DOAJ (DOAJ: Directory of Open Access Journals), Library and Archives Canada (Government of Canada) and Zenodo (CERN European Organization for Nuclear Research).

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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