Machine-assisted Composition

Machine-Assisted Composition is a procedural writing methodology in which algorithmic systems augment human authorship by generating, organizing, or refining textual content according to predefined compositional rules or data-driven models.

7

Publications

156

Citations

19

Authors

8

Institutions

Publications per year

2017–2026

2

Authors

19

  1. GM
    Gene M. Nolis

    University of Illinois Chicago, United States

    1 publications · 33 citations

    1

    h-index

  2. JA
    Jean‐Paul Allouche

    Centre National de la Recherche Scientifique, France

    1 publications · 12 citations

    1

    h-index

  3. LG
    Lisa Gerrard

    University of California, Los Angeles, United States

    1 publications · 27 citations

    1

    h-index

  4. PL
    Paul Le Blanc

    Université Savoie Mont Blanc, France

    1 publications · 13 citations

    1

    h-index

  5. TJ
    Tom Johnson

    Roquette Frères (France), France

    1 publications · 12 citations

    1

    h-index

1–5 of 19

Venues

  1. Journal of the American Chemical Society

    JACS · 1 publications · 33 citations

    1

    h-index

  2. 1

    h-index

  3. College Composition and Communication

    CCC · 1 publications · 27 citations

    1

    h-index

  4. 1

    h-index

  5. Journal of New Music Research

    1 publications · 12 citations

    1

    h-index

1–5