What's inside a voice agent pipeline: every stage from audio in to audio out

Voice agents operate through seven connected stages—noise handling, speech-to-text, turn detection, LLM processing, tool calls, text-to-speech, and transport or telephony—with perceived latency depending on how efficiently each stage streams into the next. AssemblyAI positions its offerings as the speech layer, providing Voice Focus noise isolation, Universal-3.6 Pro Realtime transcription and semantic turn detection, optional LLM Gateway access, and a Text-to-Speech API, while orchestrators such as LiveKit, Pipecat, Vapi, or custom systems retain responsibility for conversation logic, prompts, tools, barge-in policies, playback, and telephony. The post emphasizes configurable speech features including keyterm prompting, agent_context, multilingual recognition, silence-window controls, and entity-aware endpointing, citing internal and external benchmarks to support accuracy and latency claims. It also stresses production practices such as validating tool-call arguments, logging speech and LLM events under shared call IDs, handling interruptions carefully, terminating unused sessions, and ensuring that every provider in a healthcare workflow has appropriate PHI safeguards. Pricing is presented as modular, with streaming transcription billed at $0.45 per hour plus optional add-ons, reinforcing the argument that organizations can independently configure, monitor, or replace individual pipeline stages rather than rely on an opaque managed platform.

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