Audio Visualizer

A desktop audio visualizer with forensic analysis capabilities, built with Tauri, Svelte, and Rust.

Features

• Spectrogram Visualization - Real-time frequency analysis with parallel FFT processing
• Audio Playback - Play loaded audio files with waveform display
• Forensic Analysis:
  • ENF (Electrical Network Frequency) detection for 50Hz/60Hz power grid hum
  • Splice/edit detection via discontinuity analysis
  • Clipping detection
  • SNR (Signal-to-Noise Ratio) estimation
  • Dynamic range measurement
• Audio Export - Export selected time ranges to WAV files
• Multi-format Support - WAV, MP3, FLAC, OGG, and more via Symphonia

Screenshots

Coming soon

Tech Stack

Frontend:

• Svelte 5
• TypeScript
• Vite

Backend:

• Rust
• Tauri 2.0
• Symphonia (audio decoding)
• RealFFT (FFT processing)
• Rayon (parallel processing)
• Hound (WAV export)

Prerequisites

• Node.js (v18+)
• Rust (latest stable)
• Tauri prerequisites for your platform

Linux (Ubuntu/Debian)

sudo apt update
sudo apt install libwebkit2gtk-4.1-dev build-essential curl wget file \
  libxdo-dev libssl-dev libayatana-appindicator3-dev librsvg2-dev \
  libasound2-dev

macOS

xcode-select --install

Windows

Install Microsoft Visual Studio C++ Build Tools

Installation

# Clone the repository
git clone https://github.com/dojevou/audio_visualizer_tauri.git
cd audio_visualizer_tauri

# Install frontend dependencies
cd frontend
npm install

# Run in development mode
npm run tauri dev

Building for Production

cd frontend
npm run tauri build

The built application will be in frontend/src-tauri/target/release/bundle/.

Usage

1. Click Import to load an audio file
2. The spectrogram will be computed automatically
3. Use the playback controls to navigate the audio
4. Click Analyze to run forensic analysis
5. Select a time range and click Export to save a portion

Forensic Analysis Details

ENF Detection

Detects presence of power grid hum (50Hz or 60Hz) which can be used to verify recording authenticity and estimate recording location/time.

Splice Detection

Identifies potential edit points by analyzing sample discontinuities that exceed local statistical norms.

Quality Metrics

• SNR: Estimated signal-to-noise ratio in dB
• Dynamic Range: Peak-to-RMS ratio in dB
• Clipping: Detects samples exceeding 99% of full scale

Project Structure

audio_visualizer_tauri/
├── frontend/
│   ├── src/              # Svelte frontend
│   │   ├── App.svelte    # Main application
│   │   └── lib/          # Utilities (logger, etc.)
│   ├── src-tauri/        # Rust backend
│   │   ├── src/main.rs   # Tauri commands & audio processing
│   │   └── Cargo.toml    # Rust dependencies
│   └── package.json      # Node dependencies
└── README.md

License

MIT