C++ library for audio and music analysis, description and synthesis, including Python bindings
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Updated
Jun 5, 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
A tutorial for using Essentia in Python
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
Audio sample classification app for better library exploration during music production.
🎹🎵🎶 A platform to make Original and Cover Visible and Valuable.
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"
Estimate the main melody from streaming audio.
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.
Categorize audio files by genre effortlessly. Use Dockerized environment and API to classify music genres.
Essentia Music Extractor wrapped in an easy-to-use iOS framework
Music playing bot using machine learning and audio processing principles
🐳 Custom Essentia build to support high-level model classification and Chromaprint calculations in essentia_streaming_extractor_music
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