From the 1 of 4 linked papers with an AI index.
4 papers
MetaPerch: Learning from metadata for bioacoustics foundation models
Mustafa Chasmai, Vincent Dumoulin, Jenny Hamer
The paper presents MetaPerch, a bioacoustic foundation model that uses recording metadata (e.g., location, time) as auxiliary supervision to improve species identification performa…
Perch 2.0: The Bittern Lesson for Bioacoustics
Bart van Merriënboer, Vincent Dumoulin, Jenny Hamer +3
Perch is a performant pre-trained model for bioacoustics. It was trained in supervised fashion, providing both off-the-shelf classification scores for thousands of vocalizing speci…
Perch 2.0 transfers 'whale' to underwater tasks
Andrea Burns, Lauren Harrell, Bart van Merriënboer +3
Perch 2.0 is a supervised bioacoustics foundation model pretrained on 14,597 species, including birds, mammals, amphibians, and insects, and has state-of-the-art performance on mul…
The Search for Squawk: Agile Modeling in Bioacoustics
Vincent Dumoulin, Otilia Stretcu, Jenny Hamer +16
Passive acoustic monitoring (PAM) has shown great promise in helping ecologists understand the health of animal populations and ecosystems. However, extracting insights from millio…