Loud Mouth

Made with ❤️ for language learners

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A desktop language learning application that helps you learn vocabulary from video content using scientifically-proven spaced repetition techniques. Combine entertainment with effective language learning by extracting vocabulary from videos with dual-language subtitles.

Features

Video-Based Learning

• Upload and manage your video library with dual-language subtitles
• Click on any subtitle word to instantly extract vocabulary
• Context-aware learning with sentence examples from actual content

Spaced Repetition System

• Review vocabulary using the Ebbinghaus forgetting curve algorithm
• Optimized review schedule: Day 0, 1, 3, 7, 14, 30
• Smart tracking of your learning progress

Progress Tracking

• Comprehensive analytics dashboard
• Monitor your learning journey over time
• Track vocabulary acquisition and retention rates

Prerequisites

Before you begin, ensure you have the following installed:

• Node.js (v18 or higher) - Download
• pnpm (v8 or higher) - Install with npm install -g pnpm
• Rust (latest stable) - Install via rustup
• Tauri Prerequisites - Follow the Tauri prerequisites guide for your operating system

Installation

1. Clone the repository:

   git clone https://github.com/meatballG1210/loud-mouth-tauri.git
   cd loud-mouth-tauri

2. Install frontend dependencies:

   pnpm install

3. Configure environment variables:

   Copy the .env.example file to create your own .env file:

   cp .env.example .env

   Then edit .env and add your API keys:

   Required:

   • VITE_OPENAI_API_KEY - Your OpenAI API key for translation and vocabulary features
     • Get your API key from OpenAI Platform
     • The app uses OpenAI's API for automatic translations and intelligent vocabulary extraction

   Important: Never commit your .env file to version control. It's already included in .gitignore.

4. Set up the database:

   The SQLite database will be automatically initialized on first run. Database migrations are handled by Diesel and will run automatically.

Getting Started

Development Mode

Run the application in development mode with hot-reload:

pnpm tauri dev

This will:

• Start the Vite development server
• Launch the Tauri application
• Enable hot-reload for both frontend and backend changes

Production Build

Build the application for production:

pnpm tauri build

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

How to Use

1. Adding Videos

1. Click the "Add Video" button on the home screen
2. Select a video file with embedded subtitles (supported formats: MP4, AVI, MKV, MOV)
3. The app will automatically:
   • Extract embedded subtitle streams from your video
   • Detect English and Chinese subtitles
   • Generate thumbnails
   • Process the video metadata

Recommended Video Specifications:

• Video Codec: H.264/AVC High 10 (10-bit), 1080p, 23.98 fps
• Audio Codec: AAC, 48 kHz, stereo
• Subtitles: mov_text / tx3g (two tracks: Chinese zho and English eng)
• Container Format: MP4, MKV, MOV, or AVI
• Maximum File Size: 4GB

Important Notes:

• Your video must have embedded subtitle streams (not separate subtitle files)
• Both English and Chinese subtitle streams should be embedded in the same video file
• Subtitle streams must be properly tagged with language codes (eng for English, zho/chi/zh for Chinese)
• Supported embedded subtitle formats: mov_text, tx3g, SRT, ASS, SSA, and other formats supported by FFmpeg
• The app automatically converts extracted subtitles to WebVTT format for internal use
• In order to disable local subtitles on macOS, please refer to this

2. Learning from Videos

1. Select a video from your library
2. Watch the video with dual subtitles displayed
3. Click on any word in the subtitles to add it to your vocabulary
4. The app automatically captures:
   • The word and its translation
   • The sentence context
   • A timestamp for review

3. Reviewing Vocabulary

1. Navigate to the "Review" section
2. The app shows you words due for review based on spaced repetition
3. For each word:
   • Try to recall the meaning
   • Reveal the answer
   • Mark whether you remembered correctly
4. The app automatically schedules the next review

4. Tracking Progress

Visit the "Progress" page to:

• View your learning statistics
• See vocabulary growth over time
• Track review completion rates
• Identify areas for improvement

Development

Frontend Development

# Run Vite dev server only
pnpm dev

# Type checking
pnpm tsc

# Build frontend
pnpm build

Backend Development

# Run Rust tests
cd src-tauri
cargo test

# Run Rust checks
cargo check

# Create a new database migration
diesel migration generate migration_name

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.