Machine Listening
Machine Listening is a computational framework within generative sound art that enables machines to analyze, interpret, and respond to audio signals through algorithmic processing, distinguishing itself from related auditory models by its focus on generative, context-aware, and often creative sonic interactions.
44
Publications
2.8K
Citations
116
Authors
56
Institutions
Publications per year
2017–2026
19
Parents
44
Detection and Classification of Acoustic Scenes and Events
Dan Stowell, Dimitrios Giannoulis, Emmanouil Benetos et al. · IEEE Transactions on Multimedia · 2015 · 595 citations · Full text
Scaper: A library for soundscape synthesis and augmentation
Justin Salamon, Duncan MacConnell, Mark Cartwright et al. · 2017 · 209 citations
Juan Pablo Bello, Claudio Silva, Oded Nov et al. · Communications of the ACM · 2019 · 192 citations
Engineering, Environmental Engineering, Environmental Sciences +17
Sound ideas: music, machines, and experience
Choice Reviews Online · 2006 · 177 citations
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56
New York University
New York, United States
6 h-index
25 publications
3K citations

Imperial College London
London, United Kingdom
3 h-index
4 publications
101 citations
University of Augsburg
Augsburg, Germany
3 h-index
9 publications
257 citations

Cornell University
Ithaca, United States
2 h-index
4 publications
178 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
4 publications
134 citations
Queen Mary University of London
London, United Kingdom
2 h-index
5 publications
1.8K citations

University of Plymouth
Plymouth, United Kingdom
2 h-index
4 publications
170 citations
Perfect Harmony Health
Austin, United States
2 h-index
4 publications
181 citations
1–8 of 56
4 publications · 213 citations
4
h-index
2 publications · 75 citations
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AES · 2 publications · 31 citations
2
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CRO · 2 publications · 225 citations
2
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1 publications · 20 citations
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