- Python
- LLM
- Speech-to-Speech
- AI Agent
- R&D
Speech-to-Speech LLM Agent
Independently built a CLINKS Corporation proof of concept for speech-in and speech-out LLM interaction.
Overview
At CLINKS Corporation, I independently scoped and built a proof of concept for a voice agent. Speech Recognition, an LLM, and speech synthesis make up the conversation loop.
I used FastAPI and WebSocket in the prototype. I prepared it for internal evaluation and stakeholder demos.
What I Built
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Speech-to-Speech
I connected Speech Recognition, an LLM, and speech synthesis in one conversational loop.
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Independent Build
I scoped the proof of concept and implemented it independently.
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Working Prototype
I built a prototype to test the core voice interaction loop.
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Demo Preparation
I prepared the prototype for internal evaluation and demos.
Problems
- Keeping latency low in a real-time voice loop.
- Handling recognition errors without losing dialogue context.
- Balancing robustness with the pace of a proof of concept.
Results
- Built a functional speech-to-speech agent prototype.
- Tested the architecture for conversational voice interaction.
- Prepared the prototype for stakeholder demos.