Special Issue on Deep Learning for Applications in Acoustics: Modeling, Synthesis, and Listening
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Department of Information Engineering, Università Politecnica delle Marche, 60131 Ancona, Italy
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Center for Digital Music, Queen Mary University, London E1 4FZ, UK
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Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
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Authors to whom correspondence should be addressed.
Appl. Sci. 2021, 11(2), 473; https://doi.org/10.3390/app11020473
Received: 2 December 2020
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Accepted: 16 December 2020
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Published: 6 January 2021
(This article belongs to the Special Issue Deep Learning for Applications in Acoustics: Modeling, Synthesis, and Listening)
Note: In lieu of an abstract, this is an excerpt from the first page.
The recent introduction of Deep Learning has led to a vast array of breakthroughs in many fields of science and engineering [...] View Full-Text
Keywords:
deep learning; machine listening; audio processing
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
MDPI and ACS Style
Gabrielli, L.; Fazekas, G.; Nam, J. Special Issue on Deep Learning for Applications in Acoustics: Modeling, Synthesis, and Listening. Appl. Sci. 2021, 11, 473. https://doi.org/10.3390/app11020473
AMA Style
Gabrielli L, Fazekas G, Nam J. Special Issue on Deep Learning for Applications in Acoustics: Modeling, Synthesis, and Listening. Applied Sciences. 2021; 11(2):473. https://doi.org/10.3390/app11020473
Chicago/Turabian StyleGabrielli, Leonardo, György Fazekas, and Juhan Nam. 2021. "Special Issue on Deep Learning for Applications in Acoustics: Modeling, Synthesis, and Listening" Applied Sciences 11, no. 2: 473. https://doi.org/10.3390/app11020473
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