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Abstract
When we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing analysis and voice quality evaluation • Expressivity in music • Bioacoustics • Soundscapes • Hearing and hearing aids • Speech, language, and emotion recognition • Speech recognition • Emotion in speech • Speech perception • Expressivity in speech • Intelligent speech processing • Multimedia speech processing • Classification from active acoustics • Acoustic source localisation • Acoustic field prediction in ocean acoustics • Acoustical oceanography
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Authors (4)
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Zoi-Heleni Michalopoulou Prof.
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Peter Gerstoft Prof.
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Marie A. Roch Prof.
Cite as
Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1121/10.0006783
- License
- Copyright (2021 Acoustical Society of America)
Keywords
Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
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Journal of the Acoustical Society of America
no. 150,
pages 3204 - 3210,
ISSN: 0001-4966 - Language:
- English
- Publication year:
- 2021
- Bibliographic description:
- Michalopoulou Z., Gerstoft P., Kostek B., Roch M. A.: Introduction to the special issue on machine learning in acoustics// Journal of the Acoustical Society of America -Vol. 150,iss. 4 (2021), s.3204-3210
- DOI:
- Digital Object Identifier (open in new tab) 10.1121/10.0006783
- Sources of funding:
-
- Statutory activity/subsidy
- Verified by:
- Gdańsk University of Technology
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