The Google Perch bird vocalization classifier is a machine learning algorithm that can make accurate species predictions for birdsongs within soundscapes with only a small number of training samples per species, which is necessary for rare and endangered birds with few examples available for training.
The LOHE Lab, in collaboration with the Google Bioacoustics Research Group, has recently developed a method for processing the output of such machine-learning classifiers to make accurate estimates of species call densities, which can be used both as an occupancy indicator and as a measure of changes in species abundance at a site over time. We can use such tools to track population trends and make informed conservation management decisions to save native birds from extinction.
To learn more about our newly developed method, follow this link:
https://www.frontiersin.org/journals/bird-science/articles/10.3389/fbirs.2024.1380636/full
We are always looking to take on new collaborative projects!
If you have a bird monitoring project and are interested in learning how to use acoustic methods, or already have a passive acoustic monitoring program and just need the data analyzed, we would be happy to hear from you!
