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Unlabeled Echoes: Pseudo-Labels and Genus-Aware Smoothing for Bat Call Recognition

arXiv · AI, language, vision and robotics · article · Sep 8, 2026 · UTC

Passive acoustic monitoring produces far more bat recordings than experts can label. We show that simple model-generated pseudo-labels turn this surplus into effective supervision. We compare pseudo-labeling with other semi-supervised learning methods on an 18-species European corpus using only 10% of its training labels, then transfer the strongest approaches to South African field audio containing nine bat taxa and a nuisance class. Pseudo-labeling outperforms the other semi-supervised learning methods on every European measure, recovering up to 61.5% of the gap to full supervision. It trans

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