Expressive Performance Modeling is a computational framework that characterizes and synthesizes the intentional deviations from nominal musical notation—such as timing, dynamics, and articulation—introduced by performers to convey expressive intent, thereby enabling machines to generate or interpret music with human-like expressivity.
115
Publications
5.8K
Citations
170
Authors
74
Institutions
Publications per year
2017–2026
18
Parents
Publications
115
1–5 of 115
Authors
170
- GW
15
h-index
- GD
11
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- RR
10
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- WG
8
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- MG
7
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1–5 of 170
Institutions
74
Universitat Pompeu Fabra
Barcelona, Spain
11 h-index
36 publications
887 citations
Austrian Research Institute for Artificial Intelligence
Vienna, Austria
9 h-index
14 publications
893 citations
University of Padua
Padua, Italy
8 h-index
19 publications
699 citations
University of Vienna
Vienna, Austria
6 h-index
6 publications
334 citations
Johannes Kepler University of Linz
Linz, Austria
6 h-index
15 publications
729 citations
University of Sheffield
Sheffield, United Kingdom
5 h-index
6 publications
323 citations
KTH Royal Institute of Technology
Stockholm, Sweden
5 h-index
6 publications
450 citations
Carnegie Mellon University
Pittsburgh, United States
4 h-index
8 publications
367 citations
1–8 of 74
Venues
- Journal of New Music Research
15 publications · 846 citations
13
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- Computer Music Journal
8 publications · 397 citations
8
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- The Journal of the Abraham Lincoln Association
8 publications · 269 citations
8
h-index
- Music Perception An Interdisciplinary Journal
6 publications · 645 citations
6
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- The Journal of the Acoustical Society of America
JASA · 5 publications · 518 citations
5
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1–5