Computational Ethnomusicology

Computational Ethnomusicology is an academic discipline that integrates computational methods with ethnomusicological research to analyze, model, and interpret music as a cultural phenomenon, distinguished by its focus on algorithmic, data-driven, and cross-cultural approaches to musical practices and knowledge systems.

6

Publications

130

Citations

14

Authors

8

Institutions

Publications per year

2017–2026

1

Authors

14

  1. MW
    Matthew Wright

    University of Southampton, United Kingdom

    1 publications · 25 citations

    1

    h-index

  2. WA
    W. Andrew Schloss

    University of Victoria, Canada

    1 publications · 25 citations

    1

    h-index

  3. AH
    André Holzapfel

    KTH Royal Institute of Technology, Sweden

    1 publications · 15 citations

    1

    h-index

  4. FG
    Francisco Gómez

    Universidad Politécnica de Madrid, Spain

    1 publications · 44 citations

    1

    h-index

  5. JK
    James Kippen

    University of California System, United States

    1 publications · 17 citations

    1

    h-index

1–5 of 14

Venues

  1. Journal of New Music Research

    1 publications · 44 citations

    1

    h-index

  2. Applied Artificial Intelligence

    AAI · 1 publications · 16 citations

    1

    h-index

  3. Music Perception An Interdisciplinary Journal

    1 publications · 17 citations

    1

    h-index

  4. Queen Mary Research Online (Queen Mary University of London)

    Repository · 1 publications · 15 citations

    1

    h-index

  5. Zenodo (CERN European Organization for Nuclear Research)

    Repository · 1 publications · 25 citations

    1

    h-index

1–5