𝗩𝗼𝗶𝗰𝗲 𝗔𝗜: 𝗡𝗟𝗨 (𝗡𝗮𝘁𝘂𝗿𝗮𝗹 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴) - 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗠𝗲𝗮𝗻𝘁

What happens after the text arrives from ASR.

🗣️ Say you tell a voice assistant:
"Book me a flight to Paris next Friday"

ASR does its job and converts that into text.

But at this point, the system still doesn’t really understand anything.
It doesn’t know:
🔹what you’re trying to do.
🔹which parts of the sentence matter.
🔹or what information is missing.

That’s where NLU (Natural Language Understanding) comes in.

Here’s what NLU figures out behind the scenes:

1️⃣ - 𝗜𝗻𝘁𝗲𝗻𝘁 𝗖𝗹𝗮𝘀𝘀𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻
What are you trying to do?
→ You want to book a flight.

2️⃣ - 𝗘𝗻𝘁𝗶𝘁𝘆 𝗘𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻- details (entities)
→ destination: Paris
→ date: next Friday

3️⃣ And finally - 𝗦𝗹𝗼𝘁 𝗙𝗶𝗹𝗹𝗶𝗻𝗴 - what’s missing
→ where are you flying from?

So the system knows it needs to ask a follow-up.

That's the moment where the conversation starts to feel natural instead of scripted.

With models like GPT-4 or Claude, etc, a lot of this NLU work can now happen in one step without training separate intent classifiers or entity models. The model reasons about intent, details, and gaps together.

That’s a big reason modern Voice AI agents feel more flexible than the older "say it exactly this way" systems.