LANTERN

Language Analysis of Text Retell Networks

A desktop application for audio transcription, document comparison, and linguistic network analysis using local Whisper AI models.

Features

🎙️ Local Audio Transcription

• Transcribe audio files using OpenAI's Whisper model
• 100% local processing - no cloud APIs required
• Multiple model options (tiny, base, small, medium, large)
• Support for various audio formats (MP3, WAV, M4A, FLAC, OGG, etc.)

📊 Word Co-occurrence Analysis

• Generate co-occurrence matrices from transcriptions
• Customizable window sizes and minimum frequency thresholds
• Visual heatmaps and relationship graphs

🔗 Network Metrics

• Compute graph-theoretic metrics:
  • Modularity (community structure)
  • Entropy (information content)
  • Global efficiency (connectivity)
  • Diameter (network size)
  • Average shortest path length
• Analyze linguistic network properties

📝 Document Comparison

• Compare multiple transcription documents
• Side-by-side visualization
• Highlight differences and similarities

🎨 Interactive Visualizations

• Word relationship networks
• Co-occurrence heatmaps
• Network graph visualizations

Download & Installation

Quick Start

1. Download the installer for your platform from Releases
2. Install following platform-specific instructions
3. Install dependencies (Python, ffmpeg, Python packages)
4. Launch the application

See INSTALLATION.md for detailed installation instructions.

System Requirements

• OS: macOS 10.15+, Windows 10+, or Linux (Ubuntu 20.04+)
• RAM: 4GB minimum, 8GB recommended
• Disk: 2GB free space
• Python: 3.8 or higher
• ffmpeg: Required for audio processing

For Developers

Development Setup

# Clone the repository
git clone <repository-url>
cd ebrltranscriptionUI

# Install dependencies
npm install
cd backend && pip3 install -r requirements.txt && cd ..

# Start development servers
./start.sh

The application will be available at:

• Frontend: http://localhost:5173
• Backend API: http://127.0.0.1:5000

Project Structure

ebrltranscriptionUI/
├── src/                      # React frontend source
│   ├── components/          # UI components
│   ├── pages/              # Page components
│   ├── services/           # API services
│   └── utils/              # Utility functions
├── backend/                 # Python Flask backend
│   ├── server.py           # Main server file
│   ├── requirements.txt    # Python dependencies
│   └── build_backend.py    # Backend build script
├── electron/               # Electron main process
│   ├── main.cjs           # Main process entry
│   └── preload.cjs        # Preload script
├── public/                # Static assets
└── dist/                  # Built frontend (generated)

Building for Distribution

See PACKAGING.md for detailed packaging instructions.

Quick build:

# Build for current platform
npm run package:mac    # macOS
npm run package:win    # Windows
npm run package:linux  # Linux

# Build for all platforms
npm run package:all

Available Scripts

• npm run dev - Start Vite development server
• npm run build - Build frontend for production
• npm run backend:build - Build backend executable
• npm run electron:dev - Run Electron in development mode
• npm run electron:build:mac - Build macOS app
• npm run electron:build:win - Build Windows installer
• npm run electron:build:linux - Build Linux AppImage
• ./start.sh - Start both frontend and backend for development

Technology Stack

Frontend

• React 18 - UI framework
• TypeScript - Type safety
• Vite - Build tool
• TailwindCSS - Styling
• Radix UI - Component primitives
• React Query - Data fetching
• React Router - Navigation
• Recharts - Data visualization

Backend

• Python 3 - Runtime
• Flask - Web framework
• OpenAI Whisper - Speech recognition
• Pandas - Data processing
• NumPy - Numerical computing
• NetworkX - Graph analysis

Desktop

• Electron 28 - Desktop framework
• electron-builder - Packaging

Privacy & Security

LANTERN is designed with privacy in mind:

• ✅ 100% Local Processing: All transcription happens on your machine
• ✅ No Cloud APIs: No data sent to external servers
• ✅ No Internet Required: Works completely offline (after initial install)
• ✅ Your Data Stays Yours: Files never leave your computer

Use Cases

• Research: Analyze interview transcriptions, focus groups, oral histories
• Education: Study language patterns, vocabulary usage, speech analysis
• Accessibility: Generate transcripts for audio/video content
• Content Creation: Transcribe podcasts, lectures, meetings
• Linguistics: Study word relationships, network structures, language patterns

License

Copyright © 2025 Education and Brain Sciences Research Lab, Vanderbilt University

[License details here]

Credits

Developed by: Armaan Parikh Organization: Education and Brain Sciences Research Lab (EBRL), Vanderbilt University Contact: armaan.c.parikh@vanderbilt.edu

Built With

• OpenAI Whisper - Speech recognition
• Electron - Desktop framework
• React - UI framework
• Flask - Backend framework
• NetworkX - Graph analysis

Support

For issues, questions, or feature requests:

• Email: armaan.c.parikh@vanderbilt.edu
• Issues: GitHub Issues
• Documentation: See INSTALLATION.md and PACKAGING.md

Roadmap

• Additional Whisper model options
• Batch processing for multiple files
• Export results to various formats (PDF, CSV, JSON)
• Custom vocabulary/language models
• Multi-language support
• Advanced network visualization options
• Plugin system for custom analysis

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

Changelog

Version 1.0.0 (January 2025)

• Initial release
• Local Whisper transcription
• Co-occurrence matrix generation
• Network metrics computation
• Document comparison
• Electron desktop application
• macOS, Windows, Linux support

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LANTERN - Illuminating language networks through local AI analysis