Active learning for sound event classification using Monte-Carlo dropout and PANN embeddings

Shishkin, S., Hollosi, D., Doclo, S. et al. (1 more author) (2021) Active learning for sound event classification using Monte-Carlo dropout and PANN embeddings. In: Font, F., Mesaros, A., Ellis, D.P.W., Fonseca, E., Fuentes, M. and Elizalde, B., (eds.) Proceedings of the 6th Workshop on Detection and Classication of Acoustic Scenes and Events (DCASE 2021). 6th Workshop on Detection and Classification of Acoustic Scenes and Events, DCASE 2021, 15-19 Nov 2021, Virtual conference. DCASE Workshop Proceedings . DCASE , pp. 150-154. ISBN 978-84-09-36072-7

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
Editors:
  • Font, F.
  • Mesaros, A.
  • Ellis, D.P.W.
  • Fonseca, E.
  • Fuentes, M.
  • Elizalde, B.
Copyright, Publisher and Additional Information:

© 2021 The Authors. This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit: http://creativecommons.org/licenses/by/4.0/

Keywords: sound event classification; active learning; Monte Carlo dropout; self-training; transfer learning
Dates:
  • Published: 15 November 2021
  • Published (online): 15 November 2021
  • Accepted: 14 September 2021
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 06 Oct 2021 10:35
Last Modified: 07 Nov 2022 15:46
Status: Published
Publisher: DCASE
Series Name: DCASE Workshop Proceedings
Refereed: Yes
Identification Number: 10.5281/zenodo.5770113
Related URLs:
Open Archives Initiative ID (OAI ID):

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