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DeepMind Unveils Perch 2.0 to Accelerate Bioacoustic Wildlife Monitoring

It is available on Kaggle, allowing rapid analysis of audio recordings for birds, mammals, underwater species.

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Overview

  • The Perch 2.0 update doubles its training dataset with public recordings of birds, mammals, amphibians, human-made noise and other taxa.
  • Enhanced off-the-shelf bird species recognition and new underwater adaptability enable accurate detection in environments such as coral reefs.
  • Agile modeling uses vector search with active learning to let users build custom species classifiers from a single example in under an hour.
  • Early adopters have already discovered a new Plains Wanderer population and detected Hawaiian honeycreeper calls up to 50 times faster than manual review.
  • The open-source Kaggle release promotes collaboration and integration with tools like Cornell’s BirdNet Analyzer for real-time biodiversity monitoring.