MTG/essentia

Health v2 · maintenance only

Adoption not part of the score

3705 stars · 631 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Essentia is an open-source C++ library for audio analysis and music information retrieval, offering a large collection of reusable DSP algorithms and music descriptors, with Python bindings and prebuilt command-line extractors. It supports fast prototyping, research experiments, and large-scale industrial applications across Linux, macOS, Windows, iOS, and Android.

Use cases

• extract music descriptors like tempo, key, and loudness from audio files
• compute spectral and tonal features for music information retrieval research
• run audio classification models with essentia-tensorflow in Python
• batch-analyze large music catalogs with command-line extractors
• prototype audio analysis pipelines in Python notebooks
• visualize audio features in Sonic Visualiser via the Vamp plugin

When to choose

• you need robust, optimized audio/music feature extraction in C++ or Python
• you want out-of-the-box music descriptors without writing DSP code
• you are doing MIR research or building large-scale audio analysis services

When to avoid

• you need a permissive license - Essentia is AGPLv3
• you need real-time low-latency audio synthesis rather than analysis
• you only need simple playback or recording functionality

Facets

library · maturity stable

audio-processing machine-learning nlp machine-learning data-science windows python cpp cross-platform music-information-retrieval dsp audio-analysis music-descriptors tensorflow vamp-plugin feature-extraction audio linux macos ios android

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