GrunCrow/BIRDeep_BirdSongDetector_NeuralNetworks
Repository for the neural networks and models created for the BIRDeep project
This project helps ecologists and conservationists analyze large volumes of audio recordings collected from the field. It takes raw environmental audio files and identifies segments containing bird vocalizations, then classifies the bird species present. This dramatically speeds up the process of monitoring bird communities by automating what was previously a time-consuming manual task.
Use this if you conduct passive acoustic monitoring and need an automated way to detect bird songs and identify species from vast amounts of audio data.
Not ideal if your primary interest is in non-avian species or if you require real-time, on-device detection without post-processing capabilities.
Stars
13
Forks
2
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Nov 05, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/GrunCrow/BIRDeep_BirdSongDetector_NeuralNetworks"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
birdnet-team/BirdNET-Analyzer
BirdNET analyzer for scientific audio data processing.
tphakala/birdnet-go
Realtime BirdNET soundscape analyzer
birdnet-team/birdnet
A Python library for identifying bird species by their sounds.
DrCoffey/DeepSqueak
DeepSqueak v3: Using Machine Vision to Accelerate Bioacoustics Research
ear-team/bambird
Unsupervised classification to improve the quality of a bird song recording dataset....