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Essentia: C++ library for audio analysis and music information retrieval, README overview

Public record src_01M6TVMYT0M9X5J9D9GRN60FPG, revision 1. Source and rights labels remain attached. Linked media has not been viewed by opening this page.

# Essentia: C++ library for audio analysis and music information retrieval, README overview

- id: src_01M6TVMYT0M9X5J9D9GRN60FPG
- type: source · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=source_inspected, execution=not_run, review=unreviewed
- categories: T14 · tags: none
- updated: 2026-11-07T11:17:39.741Z
- url: https://veyrul.com/sources/src_01M6TVMYT0M9X5J9D9GRN60FPG

The README describes Essentia as an open-source C++ library for audio analysis and audio-based music information retrieval, released under the Affero GPLv3 license.
It contains reusable algorithms for audio input/output, signal processing, statistics and a large set of spectral, temporal, tonal and high-level music descriptors.

Source: https://github.com/mtg/essentia

What it supplies: The README describes Essentia as an open-source C++ library for audio analysis and audio-based music information retrieval, released under the Affero GPLv3 license.
It contains reusable algorithms for audio input/output, signal processing, statistics and a large set of spectral, temporal, tonal and high-level music descriptors.

Useful for: - Compute music descriptors from audio using the library in C++ or Python for prototyping and research experiments.
- Run predefined command-line extractors to compute common music descriptors without writing code.
- Visualise results in Sonic Visualiser using the included Vamp plugin.

First action: - On Linux x86_64 or i686, install the Python package with pip install essentia, or pip install essentia-tensorflow.
- Or use the Docker images, or download prebuilt static binaries of some command-line extractors instead of installing the whole library.
- Follow the Python quick start, the online tutorial or the Jupyter notebook, or use the command-line extractors.

Prerequisites and limits: The README says Essentia is cross-platform on Linux, macOS, Windows, iOS and Android and names the pip route for Linux x86_64 and i686. It says to install from master for the latest updates, lists official releases on GitHub, and warns that behaviour can differ between versions.

- Descriptor outputs can differ between Essentia versions, so record the version you use.
- The README gives pip installation only for Linux x86_64 and i686; other platforms need the installation guide, which was not read.
- The README does not list the descriptors or algorithms individually.

The README says Essentia is released under the Affero GPLv3 license. That licence has network-use obligations beyond the ordinary GPL, so read the licence before using it in a service. The licence file was not read here. Audio you analyse carries its own rights.

Written from the README text only. Statements are as the README gives them; nothing was installed or run and no audio was analysed.
Based on README text only; the documentation site, the installation guide, the licence file and the code were not read. No install or run was made.

Source inspected: https://raw.githubusercontent.com/MTG/essentia/23ae7baddecfc3227ba23ad69fa11f73ac5293a4/README.md ; 4251 bytes ; sha256 39f559194a4f6055a5daeb34699033216e86771ff55563b033953df932c9d420 ; 11 exact pinned excerpts in the draft pin map

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Rights:
- documentation: license=unknown hosting=permitted redistribution=permitted modification=permitted training=unknown · Only the team-authored original attributed summary and links are covered. Upstream papers, tutorials, code, models, weights and media retain their separate terms; no source-text/media redistribution right is implied.

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