🚀 Scribe Backend

Node.js + Express backend server for the Tongues real-time audio translation application.

✨ Features

• 🎤 Real-time Audio Processing - WebSocket-based audio streaming
• 🌍 Multi-language Support - 12+ languages for translation
• 🔄 Live Translation Pipeline - Ready for AI service integration
• 📡 Socket.IO Integration - Low-latency real-time communication
• 🚀 Express.js REST API - Clean, modular API endpoints
• 🔒 CORS Enabled - Secure frontend integration

🚀 Quick Start

Prerequisites

• Node.js (v18 or higher)
• npm or yarn

Installation

# Install dependencies
npm install

# Start development server
npm run dev

# Start production server
npm start

The server will be available at http://localhost:3001

🏗️ Architecture

• Express.js for REST API endpoints
• Socket.IO for real-time WebSocket communication
• Web Audio Processing pipeline ready for AI integration
• Modular Design for easy service integration
• CORS Configuration for frontend connectivity

🔌 Frontend Integration

This backend connects to the Tongues frontend service via WebSocket. The frontend should be running on http://localhost:5173 for full functionality.

📡 API Endpoints

Health Check

• GET /api/health - Server status and active connections

Languages

• GET /api/languages - List of supported languages

🔌 WebSocket Events

Client to Server

• audioStream - Send audio data for translation
• stopStreaming - Stop audio processing

Server to Client

• translation - Receive translated text
• error - Error messages
• connect - Connection established
• disconnect - Connection closed

🤖 AI Integration

The processAudioStream function in server.js is where you'll integrate with AI services:

Speech-to-Text Options:

1. Google Speech-to-Text - High accuracy, supports 120+ languages
2. OpenAI Whisper - Excellent quality, good for multiple languages
3. Azure Speech Services - Enterprise-grade, good integration
4. Amazon Transcribe - AWS ecosystem integration

Translation Options:

1. Google Translate API - 100+ languages, good accuracy
2. DeepL API - High quality for European languages
3. OpenAI GPT - Context-aware translations
4. Microsoft Translator - Good enterprise integration

Example Integration:

// Google Speech-to-Text + Google Translate
const speech = require('@google-cloud/speech');
const {Translate} = require('@google-cloud/translate').v2;

async function processAudioStream(audioData, sourceLanguage, targetLanguage) {
  // 1. Convert audio data to proper format
  const audioBuffer = Buffer.from(audioData);
  
  // 2. Speech-to-Text
  const speechClient = new speech.SpeechClient();
  const [response] = await speechClient.recognize({
    audio: { content: audioBuffer.toString('base64') },
    config: {
      encoding: 'LINEAR16',
      sampleRateHertz: 16000,
      languageCode: sourceLanguage,
    },
  });
  
  const transcription = response.results
    .map(result => result.alternatives[0].transcript)
    .join('\n');
  
  // 3. Translation
  const translate = new Translate();
  const [translation] = await translate.translate(transcription, targetLanguage);
  
  return translation;
}

🛠️ Development

# Development mode with auto-reload
npm run dev

# Production mode
npm start

# Check server health
curl http://localhost:3001/api/health

📁 Project Structure

├── server.js              # Main server with Socket.IO
├── package.json           # Dependencies and scripts
└── README.md              # This file

🌐 Supported Languages

• 🇺🇸 English (en)
• 🇪🇸 Spanish (es)
• 🇫🇷 French (fr)
• 🇩🇪 German (de)
• 🇮🇹 Italian (it)
• 🇵🇹 Portuguese (pt)
• 🇷🇺 Russian (ru)
• 🇯🇵 Japanese (ja)
• 🇰🇷 Korean (ko)
• 🇨🇳 Chinese (zh)
• 🇸🇦 Arabic (ar)
• 🇮🇳 Hindi (hi)

🔧 Environment Variables

Create a .env file:

PORT=3001
NODE_ENV=development
# Add your AI service API keys here
GOOGLE_APPLICATION_CREDENTIALS=path/to/credentials.json
OPENAI_API_KEY=your_openai_key

🚀 Production Deployment

1. Set NODE_ENV=production
2. Use a process manager like PM2
3. Set up reverse proxy (nginx/Apache)
4. Configure SSL certificates
5. Set up environment variables for API keys

🔒 Security Considerations

• Implement rate limiting
• Add authentication for API endpoints
• Validate audio data size and format
• Use HTTPS in production
• Implement proper error handling
• Add logging and monitoring

🤝 Contributing

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

📄 License

This project is licensed under the ISC License.

---

Part of the Tongues Audio Translation Platform