This project implements offline Automated Speech Recognition (ASR) capabilities for the Sunbird ALL platform, enhancing language learning through interactive exercises and real-time feedback.
- Offline ASR with ≥ 90% accuracy in multiple languages
- Real-time speech recognition and feedback
- Interactive language learning exercises
- Progress tracking dashboard
- Cross-platform support (Web and Mobile)
.
├── backend/ # Python backend services
│ ├── app/ # Main application code
│ ├── models/ # ASR models and ML components
│ ├── tests/ # Backend tests
│ └── Dockerfile # Backend container configuration
├── frontend/ # React/React Native frontend
│ ├── web/ # React web application
│ ├── mobile/ # React Native mobile app
│ └── shared/ # Shared components and utilities
└── docker-compose.yml # Container orchestration
- Python 3.8+
- Node.js 16+
- Docker and Docker Compose
- React Native development environment (for mobile)
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Navigate to the backend directory:
cd backend -
Create and activate a virtual environment:
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
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Install dependencies:
pip install -r requirements.txt
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Navigate to the frontend directory:
cd frontend/web # or frontend/mobile for mobile app
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Install dependencies:
npm install
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Start the backend services:
docker-compose up -d
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Start the frontend development server:
# For web cd frontend/web npm start # For mobile cd frontend/mobile npm run android # or npm run ios
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Backend:
- Python 3.8+
- FastAPI
- Vosk (Offline ASR Engine)
- SQLAlchemy
- Docker
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Frontend:
- React (Web)
- React Native (Mobile)
- TypeScript
- Material-UI
- Redux Toolkit