Voice Agent Architecture: STT, LLM, and TTS Pipelines Explained

Voice agents, essential for real-time audio processing, rely on a core architecture of speech-to-text (STT), large language models (LLM), and text-to-speech (TTS) components to transcribe, interpret, and vocalize responses. Effective voice agent design involves selecting the right models and understanding the flow of audio through the system to manage latency and enhance user experience. The text outlines different pipeline architectures—sequential and streaming—with streaming being optimal for minimizing latency and promoting natural conversations. It highlights the importance of turn detection mechanisms like voice activity detection (VAD) and model-based classifiers to determine when a user has finished speaking, ensuring a fluid interaction. Furthermore, the text discusses scaling strategies such as session state management and horizontal scaling via worker pools for handling concurrent sessions, and emphasizes the importance of observability and monitoring tools to diagnose issues across distributed system layers. The guide also mentions the option between hosted and self-hosted solutions for infrastructure management, depending on specific organizational requirements.

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