BirdNET to detect bird vocalizations for research and species monitoring
Description
BirdNET quickly scans thousands of hours of forest audio recordings to detect bird calls from species that are important for forest monitoring, like American goshawks, black-backed woodpeckers, spotted owls, and willow flycatchers.
Detailed example
The model outputs text files of bird calls, which include the bird species and time that the call was recorded.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
This decreases the time and cost associated with manually listening to recordings to identify bird calls.
Controls / human review
ATO: No; PIA: Not published
Data needed
BirdNET was developed using data from the MacAulay Library of Natural Sounds at Cornell University.