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Python LLM Speech-to-Speech AI Agent R&D

Speech-to-Speech LLM Agent

Developed a comprehensive Speech-to-Speech LLM Agent system at CLINKS Corporation. Independently managed the project from initial design to implementation as a PoC.

Overview

As an R&D Product Developer Intern at CLINKS Corporation, I independently developed a comprehensive Proof of Concept (PoC) for a Speech-to-Speech LLM Agent system. This project involved the entire development lifecycle from initial design to implementation. The system is designed to facilitate natural voice interactions with an AI agent, pushing the boundaries of conversational AI interfaces.

Key Features

Speech-to-Speech

Enables natural, real-time voice interaction with the AI agent without text input.

Independent Dev

Managed the entire project lifecycle independently, from initial design to final implementation.

PoC Success

Successfully delivered a working Proof of Concept that demonstrates the core capabilities.

Upcoming Release

The demo is scheduled for public release in December, showcasing the system's capabilities.

Technologies Used

Python LLM Speech Recognition Text-to-Speech FastAPI WebSocket

Challenges Overcome

  • Minimizing latency for real-time voice interaction
  • Handling speech recognition errors and context maintenance
  • Designing a robust architecture for the agent system

Outcomes & Impact

  • Successfully developed a functional Speech-to-Speech agent PoC
  • Demonstrated the viability of the proposed architecture
  • Prepared for public demo release in December