SEABAD is a publicly released, balanced dataset of 50,000 curated 16 kHz audio clips spanning 1,677 tropical bird species, with a dual-branch curation pipeline and MobileNetV3-Small baseline reaching 99.57% accuracy.
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Bacpipe is a modular Python package that integrates state-of-the-art bioacoustic deep learning models to generate embeddings, classifier predictions, and evaluation pipelines for custom audio data.
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SEABAD: A Tropical Bird Activity Detection Dataset for Passive Acoustic Monitoring
SEABAD is a publicly released, balanced dataset of 50,000 curated 16 kHz audio clips spanning 1,677 tropical bird species, with a dual-branch curation pipeline and MobileNetV3-Small baseline reaching 99.57% accuracy.
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bacpipe: a Python package to make bioacoustic deep learning models accessible
Bacpipe is a modular Python package that integrates state-of-the-art bioacoustic deep learning models to generate embeddings, classifier predictions, and evaluation pipelines for custom audio data.