Aureal Watermark Documentation

Overview & Architecture

Aureal Watermark is an acoustic spread-spectrum watermark engine written in pure, zero-dependency JavaScript and Node.js. It embeds an invisible, cryptographically verifiable provenance signature into master audio recordings, surviving lossy re-encoding, social media transcoding, pitch-shifting, and AI voice cloning scraper pipelines.

CLI Quick Start

Get up and running in seconds. You can generate synthetic speech-like material for testing, embed unique tracking IDs, and verify audio files directly from the command line.

# 1. Synthesize 30 seconds of speech-like audio (no sample file needed)
node bin/auralwatermark.js gen test.wav --seconds 30 --rate 44100

# 2. Embed a 32-bit recipient tracking ID with your secret salt
node bin/auralwatermark.js embed test.wav marked.wav --id 1234567 --key my-secret

# 3. Verify watermark with matched filter detection
node bin/auralwatermark.js detect marked.wav --id 1234567 --key my-secret
# Outputs: detected: YES / confidence: 1.000 / ber: 0.0% / band hit: high/mid

# 4. Blind Detection: Extract embedded ID without providing expected ID
node bin/auralwatermark.js detect unknown.wav --key my-secret --json

CLI Options Reference

gen <output.wav>

Generates harmonic speech-like test audio with envelope modulation to benchmark embedding and detection without external audio files.

embed <in.wav> <out.wav> --id <uint32>

Embeds an imperceptible watermark into an existing uncompressed PCM audio file.

detect <in.wav> [--id <uint32>] [--key <s>]

Scans an audio stream for watermarks. Operates in targeted verification mode (when --id is passed) or blind extraction mode.

Web Audio & Browser DSP

Aureal provides a browser-native verifier (src/browser/aural-watermark-verify.js) that decodes and validates audio directly inside modern web browsers using standard Web Audio APIs.

import { verifyAudioBuffer } from "./src/browser/aural-watermark-verify.js";

// 1. Decode any web-supported format (MP3, AAC, FLAC, WAV, OGG)
const audioContext = new AudioContext();
const response = await fetch("streamed_audio.mp3");
const arrayBuffer = await response.arrayBuffer();
const audioBuffer = await audioContext.decodeAudioData(arrayBuffer);

// 2. Perform offline sub-second matched filter analysis
const result = verifyAudioBuffer(audioBuffer, 1234567, "my-secret-key");

if (result.detected) {
  console.log(`Watermark Validated! Confidence: ${result.confidence * 100}%`);
  console.log(`Recovered Payload ID: ${result.recoveredPayloadId}`);
} else {
  console.log("No valid watermark detected in audio stream.");
}

Node.js API Reference

Integrate directly into backend audio pipelines, streaming servers, and distribution platforms:

import { embedWatermark, detectWatermark } from "aureal-watermark";
import { readWavFile, writeWavFile } from "aureal-watermark/src/wav.js";

// Read master recording
const wav = await readWavFile("master.wav");
const fmt = { sampleRate: wav.sampleRate, channels: wav.channels };

// Embed tracking signature
const watermarkedPcm = embedWatermark(wav.samples, fmt, {
  payloadId: 987654,
  key: process.env.WATERMARK_SALT,
  strength: 0.5,
  band: "dual"
});

// Write tagged WAV file
await writeWavFile("preview_watermarked.wav", watermarkedPcm, { ...fmt, bitDepth: 16 });

// Verify watermark
const verification = detectWatermark(watermarkedPcm, fmt, {
  payloadId: 987654,
  key: process.env.WATERMARK_SALT,
  band: "auto"
});

console.log(verification);
// { detected: true, confidence: 1.0, ber: 0.0, zScore: 14.2, frameCount: 30 }

Human Auditory System (HAS) Masking

Conventional audio watermarking methods rely on simple metadata tags or naive ultrasonic chirps (> 20 kHz). However, consumer audio encoders (MP3, AAC, Opus) immediately filter out high frequencies and strip ID3 headers during transcoding.

Aureal solves this by embedding directly into the audible frequency spectrum, strictly constrained below the biological inaudibility envelope of human hearing:

Direct Sequence Spread Spectrum (DSSS)

Rather than placing watermark energy in a few concentrated frequencies, Aureal uses an orthogonal pseudo-random noise sequence to spread the 32-bit payload across thousands of frequency bins:

• The energy per frequency bin is tens of decibels lower than ambient acoustic noise.
• Lossy audio compression algorithms (MP3, AAC, YouTube, TikTok) treat the watermark as natural harmonic texture and preserve it during encoding.
• Only a decoder with the matching cryptographic seed key can de-spread and recover the embedded provenance payload.

Commercial Licensing & Enterprise SLAs

Aureal Watermark offers commercial production licenses and custom enterprise deployment models:

For complete licensing terms, procurement details, and enterprise SLAs, visit the Commercial Licensing & Pricing Page →