Algorithmic Rhythm Generation

Algorithmic Rhythm Generation is a computational method within algorithmic composition that systematically produces rhythmic structures by applying formal rules, stochastic processes, or machine learning models to distinguish itself from ad hoc or manually composed rhythmic patterns.

14

Publications

568

Citations

31

Authors

15

Institutions

Publications per year

2017–2026

2

Authors

31

  1. GT
    Godfried Toussaint

    McGill University, Canada

    2 publications · 66 citations

    2

    h-index

  2. DB
    David Bulger

    Macquarie University, Australia

    1 publications · 11 citations

    1

    h-index

  3. DM
    Dimos Makris

    Ionian University, Greece

    1 publications · 16 citations

    1

    h-index

  4. MM
    Michael Mateas

    University of California, Santa Cruz, United States

    1 publications · 108 citations

    1

    h-index

  5. RT
    Roger T. Dean

    The Heart Research Institute, Australia

    1 publications · 11 citations

    1

    h-index

1–5 of 31

Venues

  1. 2

    h-index

  2. Neural Computing and Applications

    1 publications · 16 citations

    1

    h-index

  3. Repositori digital de la UPF (Universitat Pompeu Fabra)

    Repository · 1 publications · 15 citations

    1

    h-index

  4. 1

    h-index

  5. Zenodo (CERN European Organization for Nuclear Research)

    Repository · 1 publications · 11 citations

    1

    h-index

1–5