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arXiv · 2503.15074

InsectSet459: an open dataset of insect sounds for bioacoustic machine learning

Marius Faiß·Burooj Ghani·Dan Stowell
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Abstract

Automatic recognition of insect sound could help us understand changing biodiversity trends around the world -- but insect sounds are challenging to recognize even for deep learning. We present a new dataset comprised of 26399 audio files, from 459 species of Orthoptera and Cicadidae. It is the first large-scale dataset of insect sound that is easily applicable for developing novel deep-learning methods. Its recordings were made with a variety of audio recorders using varying sample rates to capture the extremely broad range of frequencies that insects produce. We benchmark performance with two state-of-the-art deep learning classifiers, demonstrating good performance but also significant room for improvement in acoustic insect classification. This dataset can serve as a realistic test case for implementing insect monitoring workflows, and as a challenging basis for the development of audio representation methods that can handle highly variable frequencies and/or sample rates.

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Marius Faiß, Burooj Ghani, Dan Stowell. 2025-03-19. InsectSet459: an open dataset of insect sounds for bioacoustic machine learning. https://arxiv.org/abs/2503.15074

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