BirdNET for iPhone

Overview of the Project

BirdNET is an automated system that uses machine learning to identify birds from sound. It recognizes thousands of commonly encountered species across North America and Europe by learning characteristic acoustic patterns from field recordings. The system can analyze audio containing multiple species and report detections for each one found.

Learning Process

The model is trained on collections of bird vocalizations gathered from many contributors and recording sources. From those audio samples it extracts distinguishing features and builds a compact “sound profile” for each species. Over time the system improves its ability to match new recordings to the correct species, even in noisy or mixed-species environments.

What It Can Do

• Detect multiple bird species in the same recording
• Handle a catalog of roughly 3,000 common species across NA and Europe
• Build distinct acoustic profiles for each species
• Accept user-submitted audio clips for automatic identification

Key Capabilities (alternate ordering)

• Accept user-submitted audio clips for automatic identification
• Build distinct acoustic profiles for each species
• Handle a catalog of roughly 3,000 common species across NA and Europe
• Detect multiple bird species in the same recording

Recommended Alternative

If you’re looking for a more playful, interactive option, consider Toca Life World — a free creative app for building and exploring imaginative scenes and stories. It isn’t a bird-identification tool, but it’s a hands-on way to explore environments and characters.

How to Participate

Record short sound clips using any mobile device or recorder, then submit them to the system for analysis. Submissions help both you (by identifying species you’ve heard) and the project (by expanding the training dataset and improving recognition accuracy).