Contribute to BirdNET
Advancing conservation through acoustic monitoring requires a global effort. Whether you are a developer, a data scientist, or a bird enthusiast, there are many ways to help.
Code & Open Source
BirdNET is built on open-source principles. We maintain several repositories on GitHub, ranging from our core analysis engine to mobile and web implementations.
Help us improve our tools by:
- Contributing to the BirdNET-Analyzer codebase.
- Developing new integrations for R, Python, or embedded systems.
- Reporting bugs and suggesting new features on our issue trackers.
- Improving documentation to make our tools more accessible.
Data & Expertise
High-quality, annotated audio data is the backbone of BirdNET. Your recordings and expertise can directly improve the accuracy of our models.
How you can contribute data:
- Upload to Xeno-canto: Share your bird recordings on xeno-canto.org. We regularly use these recordings for model training.
- Annotated Soundscapes: If you have fully annotated soundscapes (long-form recordings with species labels and timestamps), please let us know.
- Expert Validation: Help us validate detections in your region to ensure our models reflect local biodiversity accurately.
Every recording helps us advance conservation bioacoustics. Feel free to reach out to us if you have datasets or expertise to share.
Research & Conservation
We are always looking for new ways to apply BirdNET in the field. We collaborate with researchers and conservation organizations worldwide to turn acoustic data into actionable insights.
Monitoring Projects
If you have a monitoring project that could benefit from AI expertise, we'd love to hear from you.
Funding Proposals
We are open to joint funding proposals that advance bioacoustics and conservation technology.
Interested in collaborating? Contact us to discuss your project.
Student Projects
Are you a student looking for a thesis topic? We offer projects at Chemnitz University of Technology, often in collaboration with other institutions.
- TinyML: Deploying lightweight models on embedded devices and field sensors.
- Advanced ID: Individual bird identification and bat sound identification.
- Unsupervised Learning: Species discovery and acoustic pattern recognition.
- Foundation Models: Exploring large-scale pre-training for acoustic monitoring.
Our student projects offer immediate visibility through open-source development and the chance to contribute to a project used by thousands.
Interested in a thesis project? Reach out to us with your background.
Other ways to help
If you're not a developer or data specialist, you can still support the project by donating to help cover infrastructure and research costs.
Support the project