Voice AI architecture: how STT, LLM, and TTS work together
Voice AI architecture generally follows a pipeline, speech to text converts what's said into text, a language model decides on a response, and text to speech converts that response back into audio, all repeated for each turn of the conversation.
Why the pipeline is sequential
Each stage depends on the output of the previous one, the language model can't respond until it has text to read, and text to speech can't speak until the model has generated a response, which makes minimizing delay at each individual step important for overall responsiveness.
Where streaming helps
Rather than waiting for a caller to finish speaking entirely before starting to process, or waiting for a full response before starting to speak it, many systems stream partial results between stages to reduce the perceived delay in the conversation.
Where model choice matters
The specific speech to text, language model, and text to speech providers used can significantly affect both the quality and the latency of the overall system, which is why platform providers often evaluate and combine best in class options for each stage rather than defaulting to a single vendor's full stack.
Frequently asked
It helps, but total latency also depends on the speech to text and text to speech stages, so all three need to be reasonably fast for the conversation to feel natural.
More in Technical
A voice agent system is typically built from a few connected layers, a telephony layer that handles the actual phone connection, a speech processing layer that converts audio to text and back, and a language model layer that decides what to say.
A voice agent API generally lets you send leads into a calling campaign programmatically, trigger and manage campaigns through code, and pull call data, transcripts, and outcomes back into your own systems on demand.
Voice agent webhooks send a real time notification to an endpoint you control whenever something happens, a call completes, a lead status changes, or a meeting gets booked, letting you build custom logic on top of that event instead of polling for updates.
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