Decoding Insect Song: A Multitask Semisupervised Orthoptera Bioacoustic Classifier

• URL: http://arxiv.org/abs/2606.13236v1
• Date: Thu, 11 Jun 2026 11:51:49 GMT
• Title: Decoding Insect Song: A Multitask Semisupervised Orthoptera Bioacoustic Classifier
• Abstract summary: PULSE is a semi-supervised, multi-task framework for Orthoptera bioacoustics.<n>It combines weakly-supervised species classification, self-supervised learning on unlabelled field audio, and knowledge distillation from a general-purpose bioacoustic model.
• Score: 0.6524460254566904
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Passive acoustic monitoring holds great promise for ecological inference, yet existing automated tools are typically narrowly trained and non-transferable. We address these limitations with PULSE, a semi-supervised, multi-task framework for Orthoptera bioacoustics, combining weakly-supervised species classification, self-supervised learning on unlabelled field audio, and knowledge distillation from a general-purpose bioacoustic model. Our domain-adapted specialist model outperforms a state-of-the-art general model across all metrics (macro F1: 0.21 vs. 0.07; AUC: 0.74 vs. 0.45; AP: 0.32 vs. 0.19), with active learning further raising F1 to 0.34 and AUC to 0.84. Beyond classification, the learned embeddings encode ecologically meaningful structure, exposed through an interactive visualisation tool for ecological discovery.

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