Overview
This proof-of-concept explored a more natural interface for AI agents by connecting speech recognition, large language models, and speech synthesis into a single conversational loop.
The project was scoped and implemented independently, which made architectural clarity and iteration speed just as important as the voice experience itself.
Key Features
Speech-to-Speech
Supports voice-first interaction without requiring the user to fall back to text.
End-to-End Ownership
Handled the project independently from early design decisions through implementation.
Proof of Concept
Delivered a working prototype that demonstrates the core interaction loop.
Demo Ready
Prepared the system for release demos and internal evaluation.
Technologies Used
Python LLM Speech Recognition Text-to-Speech FastAPI WebSocket
Challenges Overcome
- Reducing latency in the real-time voice loop.
- Handling recognition errors while preserving dialogue context.
- Balancing robustness with rapid prototyping speed.
Outcomes & Impact
- Delivered a functional speech-to-speech agent prototype.
- Validated the proposed architecture for conversational voice interaction.
- Prepared the system for stakeholder demos.