Librosa‐inspired Analysis in HTML5 - brookcs3/BeaatsLoops GitHub Wiki

This document outlines how to recreate a subset of Librosa's functionality using only browser APIs. The goal is lightweight audio analysis that can run directly in the client's browser without Python or heavy dependencies.

Key Techniques

  • Web Audio API – Use AudioContext and OfflineAudioContext for decoding and processing audio buffers.
  • Typed Arrays – Process raw PCM data with JavaScript arrays to compute features such as RMS and simple spectra.
  • Modular Functions – Provide utilities that mirror common Librosa helpers (load, rms, peak, spectrogram).

Example Module

The file frontend/librosaLite.js implements a few basic helpers:

import { loadAudioBuffer, computeRMS, computePeak, computeSpectrum } from './librosaLite.js';

const buffer = await loadAudioBuffer('/path/to/clip.wav');
const rms = computeRMS(buffer);
const peak = computePeak(buffer);
const spectrum = await computeSpectrum(buffer);

These functions rely purely on HTML5 APIs and should work in modern browsers (including any future "HTML6" environment). They provide enough data to drive visualizers or dynamic effects on the site.

Next Steps

  • Expand the module to calculate mel‑spectrograms or tempo using WebAssembly for heavier math.
  • Integrate the analysis results into @react-three/fiber scenes for audio‑reactive visuals.
  • Cache analysis output to avoid recomputation for returning visitors.