𝗩𝗼𝗶𝗰𝗲 𝗔𝗜: 𝗗𝗶𝗮𝗹𝗼𝗴 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 - 𝗧𝗵𝗲 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗼𝗿

Source: Dev.to

Dialog Management

We’ve talked about how Voice AI listens (ASR) and understands (NLU).
But once the system understands the user, there’s a harder question:

What should happen next?

This is where Dialog Management comes in.

It’s not about generating responses — it’s about orchestrating decisions across multiple turns.

Example

• User: “Book a flight to Paris”
• Assistant: [dest: Paris, origin: ❓] → "Where from?"
• User: “New York”
• Assistant: [all slots filled] → "NYC → Paris. Confirm?"

That decision flow is Dialog Management.

Under the hood, it handles

• Tracking conversation state across turns.
• Knowing what’s been said vs. what’s missing.
• Deciding when to ask for more information vs. when to act.
• Handling corrections and errors.
• Executing actions and tools safely.

This turns one‑shot commands into real conversations. Modern Voice AI agents may use LLMs for the language side, but a structured dialog manager remains essential for reliability and safety. Without it, even the best models feel unpredictable.

➡️ Next up: How Voice AI remembers — context & memory management.