Shishkin, S., Hollosi, D., Goetze, S. orcid.org/0000-0003-1044-7343 et al. (1 more author) (2024) Active learning for sound event classification using Bayesian neural networks with Gaussian variational posterior. In: ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP24), 14-19 Apr 2024, Seoul, South Korea. Institute of Electrical and Electronics Engineers (IEEE) , pp. 896-900. ISBN 979-8-3503-4486-8
Abstract
Manual annotation of audio material is cumbersome. Active learning aims at minimizing the annotation effort by iteratively selecting an acquisition batch of unlabeled data, asking a human to annotate the selected data and re-training a classifier until an annotation budget is depleted. In this paper we propose the Gaussian-dense active learning (GDAL) algorithm to train a sound event classifier. The classifier is a Bayesian neural network where the weights are normally distributed. This is in contrast to conventional neural networks where weights are not distributed, but have assigned values. The Bayesian nature of the classifier empowers GDAL to select acquisition batches from a set of unlabeled audio clips based on their estimated informativeness. Evaluation results on the UrbanSound8k dataset show that GDAL outperforms a state-of-the-art algorithm based on medoid active learning for all considered annotation budgets and an algorithm based on dropout active learning for sufficiently large annotation budgets.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Author(s). Except as otherwise noted, this author-accepted version of a conference paper published in International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 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: | sound event classification; active learning; Bayesian neural networks; PANN embeddings |
Dates: |
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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: | 29 Feb 2024 11:52 |
Last Modified: | 28 Mar 2024 12:31 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/ICASSP48485.2024.10446970 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:209653 |