BirdNET uses deep learning to identify 6,000+ bird species worldwide from sound. We build open-source tools that scale from a single recording to continent-wide monitoring programs — making professional bioacoustics accessible to researchers, conservationists, and citizen scientists alike.
A joint initiative of the K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab of Ornithology and Chemnitz University of Technology.
| Repository | Description | Language |
|---|---|---|
| BirdNET-Analyzer | Main analysis engine for scientific audio data — batch processing, custom training, embeddings, and more | Python, Gradio |
| birdnet | Python library for bird species identification, built for robust ecological data workflows | Python |
| birdnetR | R wrapper around the birdnet package — run BirdNET and handle results directly in R | R |
| birdnetTools | Shiny tools for summarizing, visualizing, and working with BirdNET output | R, Shiny |
| geomodel | Spatiotemporal species occurrence prediction for post-filtering BirdNET acoustic detections | Python |
| BirdBox | YOLO-based bounding box detector for bird vocalizations in spectrograms | Python |
| birdnet-V3.0-dev | CLI and GUI for BirdNET+ V3.0 developer preview models | Python, Streamlit |
| LyreBot | Interactive AI agent for bioacoustics | Python, React |
| Taxonomy | Taxonomy and species metadata for BirdNET models | Python |
| Repository | Description | Language |
|---|---|---|
| birdnet-stm32 | Training and deployment for tiny BirdNET models on STM32 hardware | Python, C++ |
| BirdNET-Tiny-Forge | Framework for creating custom birdsong loggers on low-power devices | Python, C++ |
| ecopi-rtf | Real-time frontend for ecoPi devices running BirdNET | Python, Dash |
| Repository | Description | Language |
|---|---|---|
| real-time-pwa | BirdNET Live — Real-time identification in your browser (PWA) | JavaScript |
| birdnet-website | BirdNET website codebase | Eleventy, Bootstrap |
- BirdNET App — Free mobile app for Android & iOS
- BirdNET Live — Real-time identification in your browser (works offline!)
- Browser Demo — Upload audio and analyze with TensorFlow.js
We're fortunate to have an amazing community building tools and projects with BirdNET. Check out the Showroom to see what people are creating — from HaikuBox and BirdWeather to Raspberry Pi stations and desktop apps.
We host an annual competition on Kaggle which is a great entry point for anyone new to AI-powered bioacoustics: BirdCLEF+ 2026 on Kaggle.
Interested in TinyML? Make sure to check out our TinyML competition at BioDCASE: BioDCASE Task 3.
- GitHub Discussions — Questions, ideas, and workflow tips
- r/BirdNET_Analyzer — Community subreddit for users and tinkerers
- Contribute — Code, data, or expertise
BirdNET is grounded in peer-reviewed research. Our focus is on developing reliable open-source tools that transform raw audio into publication-ready ecological data.
- Publications — Papers, conference contributions, and validation studies
- Projects Map — See how researchers worldwide use BirdNET
- K-12 Resources — Educational materials for schools
We work closely with open-source contributors who develop complementary tools:
- DBD Research Group — Additional bioacoustic tools and research
- Google Perch — Large-scale bird vocalization models
- Website: birdnet.cornell.edu
- Email: [email protected]
- About: Learn more about BirdNET
BirdNET is a research project that depends on community support. If you find our tools useful, consider making a donation to help fund model development, infrastructure, and new features.
BirdNET: The AI toolkit for conservation.
