VOICE AI SYSTEM ARCHITECTURE

Source: Dev.to

How Voice AI Agents Work

I’ve been diving deep into Voice AI Agents and decided to map out how they actually work.
When you ask Alexa or ChatGPT Voice a question and it responds intelligently, a lot is happening in that split second.

At a high level, every voice agent needs to handle three tasks:

• Listen – capture audio and transcribe it
• Think – interpret intent, reason, plan
• Speak – generate audio and stream it back to the user

Core Stages of a Voice AI Agent

A Voice AI Agent typically goes through five core stages:

1. Speech‑to‑Text (ASR) – Convert spoken audio into text.
2. Natural Language Understanding (NLU) – Identify intent and extract entities.
3. Dialog Management / Agent Logic – Reason about the appropriate action.
4. Natural Language Generation (NLG) – Produce a textual response.
5. Text‑to‑Speech (TTS) – Synthesize the response into natural‑sounding audio.

This architecture powers assistants like Alexa, Siri, Google Assistant, and modern LLM‑based voice agents such as ChatGPT Voice.

I’ve created a diagram to visualize the full end‑to‑end pipeline—from speech input to intelligent action and response. I plan to break down each component and share more on how agent‑based voice systems are built.

Which Voice AI agent do you interact with the most?