Edge-Based Real-Time Language Translation and Speech Processing System

Develop a real-time speech translation system that processes audio data locally using edge computing. The system aims to provide low-latency multilingual communication while preserving user privacy and minimizing dependency on cloud-based language processing services.

Study speech recognition and natural language processing models.

Research lightweight AI frameworks optimized for edge devices.

Design system architecture for local audio processing.

Implement speech-to-text conversion at the edge.

Integrate real-time translation models for multiple languages.

Develop text-to-speech output modules.

Optimize model size and inference speed.

Compare latency with cloud-based translation APIs.

Conduct usability testing in real conversation scenarios.

Evaluate privacy benefits of local processing.

Document performance metrics and scalability.