meyda/meyda

Health v2 · maintenance only

Adoption not part of the score

1662 stars · 107 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Meyda is a JavaScript audio feature extraction library that computes standard signal features like RMS, spectral centroid, and spectral flatness from audio buffers or real-time streams. It works both offline and in real time via the Web Audio API, in the browser and Node.js.

Use cases

• extract audio features like spectral centroid and RMS from audio in the browser
• build real-time audio visualizations with the Web Audio API
• compute audio features for machine learning on sound
• analyze wav files offline in Node.js
• get loudness and timbre statistics from microphone input
• music information retrieval in JavaScript

When to choose

• you need standardized audio features (RMS, spectral centroid, flatness, etc.) in JavaScript
• you want real-time feature extraction alongside the Web Audio API
• you need a lightweight, MIT-licensed library usable in browser and Node.js

When to avoid

• you need full MIR toolkits with things like chord detection or beat tracking
• you work in Python and want librosa's breadth of features
• you need GPU-accelerated batch feature extraction for large corpora

Facets

library · maturity stable

audio-processing machine-learning data-science machine-learning browser audio-features music-information-retrieval spectral-analysis web-audio-api real-time-audio signal-processing audio nodejs javascript typescript web

Member repositories

For agents

markdown · JSON · MCP: product_card(name="meyda/meyda")