C++ library for audio and music analysis, description and synthesis, including Python bindings
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Updated
Oct 23, 2024 - C++
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
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
The Light music visualizer v3
Harmonic-Percussive source separation using Essentia, and JUCE for the GUI
Docker container to retrieve musical information from audio data using Essentia extractors
Neural network for classifying audio samples into categories. This was my BSc final year project.
Essentia Music Extractor wrapped in an easy-to-use iOS framework
Dockerized benchmark model & API for classifying music by genre based on TensorFlow and Essentia
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