After decades of frustration, machine learning tools are unlocking a treasure trove of acoustic data for ecologists.
Last August, capping off eight years of research, the team published a paper detailing BirdVoxDetect’s machine-learning algorithms. They also released the software as a free, open-source product for ornithologists to use and adapt. In a test on a full season of migration recordings totaling 6,671 hours, the neural network detected 233,124 flight calls. In a 2022 study in the Journal of Applied Ecology, the team that tested BirdVoxDetect found acoustic data as effective as radar for estimating total biomass.
Article by Christian Elliott, illustration by Bell Hutley.
For more details on BirdVoxDetect, visit:
https://audio.ls2n.fr/birdvoxdetect-large-scale-detection-and-classification-of-flight-calls-for-bird-migration-monitoring/