Neural Performance Generation

Neural Performance Generation is a computational framework within the field of generative performance that utilizes artificial neural networks to algorithmically synthesize expressive human-like performances by modeling temporal dynamics, stylistic nuances, and contextual coherence in multimodal artistic output.

1

Publications

12

Citations

2

Authors

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Institutions

Publications per year

2017–2026

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Authors

2

  1. RB
    Roberto Bresin

    KTH Royal Institute of Technology, Sweden

    1 publications · 12 citations

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  2. GW
    Gerhard Widmer

    Johannes Kepler University of Linz, Austria

    1 publications · 12 citations

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    h-index

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