C++ library for audio and music analysis, description and synthesis, including Python bindings
JavaScript library for music/audio analysis and processing powered by Essentia WebAssembly
AudioMuse-AI is an Open Source Dockerized environment that brings automatic playlist generation to Jellyfin, Navidrome, LMS and Lyrion. Using powerful tools like Librosa and ONNX, it performs sonic analysis on your audio files locally, allowing you to curate the perfect playlist for any mood or occasion without relying on external APIs.
Jellyfin plugin for AudioMuse-AI
Methods to compute various chroma audio features and audio similarity measures particularly for the task of cover song identification
Estimate the main melody from streaming audio.
A tutorial for using Essentia in Python
Matlab implementation of the: J.R. Zapata, M. Davies and E. Gómez, "Multi-feature beat tracker," IEEE/ACM Transactions on Audio, Speech and Language Processing. 22(4), pp. 816-825, 2014"
Categorize audio files by genre effortlessly. Use Dockerized environment and API to classify music genres.
🎹🎵🎶 A platform to make Original and Cover Visible and Valuable.
The project consists in evaluating music similarity and building a genre classifier using song embeddings from GTZAN dataset extracted with Essentia’s MSD-MusiCNN model.
Reproducible research code for the experiments presented in our article "Kara1k: a karaoke dataset for cover song identification and singing voice analysis" published at IEEE ISM 2017
Docker container to retrieve musical information from audio data using Essentia extractors
Harmonic-Percussive source separation using Essentia, and JUCE for the GUI
The Light music visualizer v3
🎵 Transform Spotify playlists into a DJ-ready Rekordbox library. Automatic KEY detection (Camelot), BPM analysis, quality filtering, and smart organization. Perfect for harmonic mixing!
Music classification and discovery tool
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