On data sampling strategies for training neural network speech separation models

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Ravenscroft, J. orcid.org/0000-0002-0780-3303, Goetze, S. and Hain, T. (2023) On data sampling strategies for training neural network speech separation models. In: 2023 31st European Signal Processing Conference (EUSIPCO). 31st European Signal Processing Conference (EUSIPCO 2023), 04-08 Sep 2023, Helsinki, Finland. Institute of Electrical and Electronics Engineers (IEEE) ISBN 978-9-4645-9360-0

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Item Type: Proceedings Paper
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© 2023 The Authors. Except as otherwise noted, this author-accepted version of a proceedings paper published in 2023 31st European Signal Processing Conference (EUSIPCO) is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

Keywords: speech separation; context modelling; data sampling; speech enhancement; transformer
Dates:
  • Published: 1 November 2023
  • Accepted: 29 May 2023
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Funding Information:
Funder
Grant number
Engineering and Physical Sciences Research Council
2268977
Depositing User: Symplectic Sheffield
Date Deposited: 21 Jun 2023 12:08
Last Modified: 07 Dec 2023 12:34
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Identification Number: 10.23919/EUSIPCO58844.2023.10289800
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