BirdNET-Analyzer
BirdNET-Analyzer is the workhorse tool for large-scale bird sound analysis, built for scientific workflows and long-term monitoring.
What it does
BirdNET-Analyzer applies BirdNET models to audio recordings to detect bird vocalizations and assign species labels. It supports both interactive use and scripted batch processing, making it suitable for everything from small pilot studies to multi-year monitoring projects.
- Processes single files or entire directories of recordings.
- Outputs detections with timestamps, species labels, and confidence scores.
- Supports geographic and temporal constraints for more realistic species lists.
- Provides a GUI and command-line workflows.
Get BirdNET-Analyzer
-
Download:
BirdNET-Analyzer releases page -
Documentation:
BirdNET-Analyzer documentation -
Source code:
github.com/birdnet-team/BirdNET-Analyzer -
Python package:
birdnet-analyzer on PyPI
Key features
Large-scale processing
Designed to handle large deployments of passive acoustic recorders and thousands of hours of audio.
Advanced models
Uses the latest BirdNET models, capable of recognizing thousands of bird species worldwide.
Flexible outputs
Export detections as CSV or other formats for downstream analysis in R, Python, or GIS tools.
Community workflows
A growing set of guides and scripts from the community show how to integrate BirdNET-Analyzer into existing monitoring pipelines.
Contributing & Support
Get help / Improve BirdNET-Analyzer
- Open an GitHub Issue (search existing first).
- Use clear title, steps to reproduce, expected vs actual, logs/error messages.
- Add environment details (OS, Python version, BirdNET-Analyzer version).
- Fork and create a feature branch, then open a Pull Request.
- Keep changes focused; update docs if behavior changes.
- Reference related Issue (e.g. “Closes #123”).
- Use GitHub Discussions for Q&A and ideas.
- Tag threads (Help, Ideas, Show & Tell) appropriately.
- Join the Reddit community: r/BirdNET_Analyzer.
- Share workflows, troubleshooting tips, and results.