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.
