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Propagating variational model uncertainty for bioacoustic call label smoothing

Rizos, Georgios, Lawson, Jenna, Mitchell,, Simon L., Shah, Pranay, Wen, Xin, Banks-Leite, Cristina, Ewers, Robert, Schuller, Björn W (2024) Propagating variational model uncertainty for bioacoustic call label smoothing. Patterns (New York, N.Y.), 5 (3). Article Number 100932. E-ISSN 2666-3899. (doi:10.1016/j.patter.2024.100932) (KAR id:105474)

Abstract

Along with propagating the input toward making a prediction, Bayesian neural networks also propagate uncertainty. This has the potential to guide the training process by rejecting predictions of low confidence, and recent variational Bayesian methods can do so without Monte Carlo sampling of weights. Here, we apply sample-free methods for wildlife call detection on recordings made via passive acoustic monitoring equipment in the animals' natural habitats. We further propose uncertainty-aware label smoothing, where the smoothing probability is dependent on sample-free predictive uncertainty, in order to downweigh data samples that should contribute less to the loss value. We introduce a bioacoustic dataset recorded in Malaysian Borneo, containing overlapping calls from 30 species. On that dataset, our proposed method achieves an absolute percentage improvement of around 1.5 points on area under the receiver operating characteristic (AU-ROC), 13 points in F1, and 19.5 points in expected calibration error (ECE) compared to the point-estimate network baseline averaged across all target classes. [Abstract copyright: © 2024 The Authors.

Item Type: Article
DOI/Identification number: 10.1016/j.patter.2024.100932
Uncontrolled keywords: variational Bayesian deep learning; uncertainty propagation; adaptive label smoothing; epistemic uncertainty; calibrated deep learning; bioacoustics; wildlife call detection; passive acoustic monitoring; machine audition
Subjects: H Social Sciences
Divisions: Divisions > Division of Human and Social Sciences > School of Anthropology and Conservation > DICE (Durrell Institute of Conservation and Ecology)
Funders: Engineering and Physical Sciences Research Council (https://ror.org/0439y7842)
SWORD Depositor: JISC Publications Router
Depositing User: JISC Publications Router
Date Deposited: 11 Apr 2024 14:13 UTC
Last Modified: 05 Nov 2024 13:11 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/105474 (The current URI for this page, for reference purposes)

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