Identify birds by sound, at scale.

BirdNET uses deep learning to recognize thousands of bird species from their vocalizations, powering research, monitoring, and citizen science around the world.

BirdNET is a collaboration between the K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab of Ornithology and Chemnitz University of Technology.

What is BirdNET?

BirdNET is a research platform and family of tools that make it possible to detect, classify, and explore bird sounds using state-of-the-art neural networks.

From smartphone apps to large passive acoustic monitoring arrays, BirdNET supports workflows for birders, conservationists, and scientists.

For everyone

Mobile & web apps

Record a bird and get instant identification suggestions on iOS, Android, or the BirdNET Sound ID website.

Learn more

For research

BirdNET-Analyzer

Process large acoustic datasets, extract detections, and build sophisticated workflows for long-term biodiversity monitoring.

Explore Analyzer

For developers

Open-source tools

Python, R, embedded, and web tools let you integrate BirdNET models into your own hardware and analysis pipelines.

View tools

Explore the BirdNET ecosystem

Tools, datasets, publications, and community projects driving acoustic biodiversity insights.

Forest soundscape

BirdNET-Analyzer

The workhorse engine for applying BirdNET models to large audio datasets. Built for scientific workflows and long-term monitoring.

  • Scales from pilot studies to multi-year deployments.
  • Detections with timestamps, species labels, confidence scores.
  • Geographic + temporal filters for realistic species lists.
  • CLI and GUI workflows.
Learn more

Large-scale processing

Handles thousands of hours from passive acoustic networks.

Latest models

Recognizes thousands of species worldwide.

Flexible outputs

CSV and other formats for Python / R / GIS workflows.

Community ecosystem

Growing scripts and guides for monitoring pipelines.

Open-source tools

BirdNET models power a suite of libraries and platforms across Python, R, embedded systems, and field devices.

Explore tools

Python

birdnet

Library for ecological sound workflows.

GitHub

R

birdnetR

R wrapper for BirdNET processing & results.

GitHub

Embedded devices

BirdNET-Tiny-Forge

Create and deploy lightweight models.

GitHub

Community showroom

BirdNET powers devices, apps, and creative platforms built by a growing community.

Explore showroom

HaikuBox

Backyard station sharing clips & IDs.

Learn more

BirdNET-Pi

Raspberry Pi real-time detections.

Learn more

BirdWeather

Global real-time station map.

Learn more

Chirpity

Desktop validation tool for detections.

Learn more

BirdNET-Go

Golang implementation of BirdNET.

Learn more

ecoSound-web

Web-based ecoacoustics suite.

Learn more

More projects featured on the showroom page.

K‑12 learning

Kid‑friendly projects that connect AI, birds, and curiosity. Explore activities for classrooms and makers.

Explore K‑12

Schlaumeise

Interactive learning platform (German).

Visit schlaumeise.org

SmartFinch

Activities to explore birds, sound, and AI (English).

Visit smartfinch.org

More details and contact on the K‑12 page.