BirdNET: the global standard in animal sound identification

How can computers learn to recognize birds from sounds?

The K. Lisa Yang Center for Conservation Bioacoustics and the Chair of Media Informatics at Chemnitz University of Technology are trying to find an answer to this question. Our research is mainly focused on the detection and classification of avian sounds using machine learning – we want to assist experts and citizen scientist in their work of monitoring and protecting our birds. BirdNET is a research platform that aims at recognizing birds by sound at scale. We support various hardware and operating systems such as Arduino microcontrollers, the Raspberry Pi, smartphones, web browsers, workstation PCs, and even cloud services. BirdNET is a citizen science platform as well as an analysis software for extremely large collections of audio. BirdNET aims to provide innovative tools for conservationists, biologists, and birders alike.

Visit our BirdNET site for public demonstrations, including a live stream demo, a demo for the analysis of audio recordings, an Android and iOS app, and its visualization of submissions. All demos are based on an artificial neural network we call BirdNET. We are constantly improving the features and performance of our demos – please make sure to check back with us regularly.

BirdNET can currently identify around 3,000 of the world’s most common species. We will add more species in the near future.