Desktop application to identify bird vocalisations in lengthy audio files. Uses either BirdNET or a native AI model tuned for the calls of nocturnal migrants.
Author: Matthew Kirkland
- Uses two Machine Learning models to identify audio files based on the user's needs: BirdNET and the Nocmig model
- Supports audio input files such as WAV, MP3, MP4/M4A, AAC, Opus, Ogg, and FLAC
- Audio analysis can run in the background while exploring the application
- Tailor species detection based on the season, time of day, or a custom list of species
- Program can reduce background noise to make avian sounds more audible
- ...and more
Visit https://chirpity.mattkirkland.co.uk for platform specific installation instructions - Chirpity binaries are available for Windows, Mac and Linux platforms.
First, clone the project and install all dependencies:
git clone https://github.com/Mattk70/Chirpity-Electron
cd Chirpity-Electron
Chirpity depends on Node.js, follow the link for the download and installation instructions. Once installed, run:
npm install
Next, launch the app with:
npm start
Initialize the source directory with:
npm init
Now, install project dependencies with:
npm install --save-dev
After that, build a windows msi installer with:
npm run export
The resulting application will be saved in the "dist" folder.