Source Synthesis
Source Synthesis is a computational methodology within acoustic source modeling that generates artificial representations of sound sources by integrating physical, statistical, or machine learning-based principles to replicate or simulate the characteristics of real-world acoustic emissions.
151
Publications
5.2K
Citations
362
Authors
140
Institutions
Publications per year
2017–2026
50
Parents
151
GANSynth: Adversarial Neural Audio Synthesis
Jesse Engel, Kumar Krishna Agrawal, Shuo Chen et al. · arXiv (Cornell University) · 2019 · 240 citations · Full text
Music Source Separation in the Waveform Domain
Alexandre Défossez, Nicolas Usunier, Léon Bottou et al. · arXiv (Cornell University) · 2019 · 185 citations · Full text
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140
Google (United States)
Mountain View, United States
5 h-index
16 publications
780 citations
Technische Universität Berlin
Berlin, Germany
5 h-index
8 publications
152 citations

National Institute of Informatics
Tokyo, Japan
4 h-index
13 publications
905 citations

University of Edinburgh
Edinburgh, United Kingdom
4 h-index
6 publications
214 citations
University of California, Los Angeles
Los Angeles, United States
4 h-index
7 publications
165 citations

Institut de Recherche et Coordination Acoustique Musique
Paris, France
3 h-index
5 publications
101 citations

Nagoya Institute of Technology
Nagoya, Japan
3 h-index
12 publications
221 citations
Baidu (China)
Beijing, China
3 h-index
10 publications
506 citations
1–8 of 140
Repository · 17 publications · 970 citations
13
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8 publications · 613 citations
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JASA · 8 publications · 336 citations
8
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TASLP · 7 publications · 132 citations
6
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Repository · 4 publications · 76 citations
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