𝗩𝗼𝗶𝗰𝗲 𝗔𝗜: 𝗡𝗟𝗚 -𝗧𝘂𝗿𝗻𝗶𝗻𝗴 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 𝗜𝗻𝘁𝗼 𝗪𝗼𝗿𝗱𝘀

Voice AI listens (ASR), understands (NLU), and decides (Dialog Management).

But decisions aren’t responses. The system knows: ▶️ Action: inform ▶️ Flight: booked ▶️ Destination: Paris ▶️ Date: Dec 20 ▶️ Confirmation: AB123

That’s not what we say to a user.

This is where 𝗡𝗟𝗚 (Natural Language Generation) comes in.

Natural Language Generation (NLG)

It transforms structured data into natural speech: Example: 🤖 “Great news! Your flight to Paris on December 20th is confirmed. Your confirmation number is AB123. Have a wonderful trip!”

𝗧𝗵𝗲 𝗡𝗟𝗚 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲: 1️⃣ 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 🔹”What information to convey?” 🔹Select facts, order them, prioritize. 2️⃣ 𝗦𝗲𝗻𝘁𝗲𝗻𝗰𝗲 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 🔹”How to structure it?” 🔹One sentence or multiple? 🔹Combine facts? 3️⃣ 𝗦𝘂𝗿𝗳𝗮𝗰𝗲 𝗥𝗲𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 🔹”What exact words to use?” . 🔹Grammar, vocabulary, tone, fluency.

𝗧𝗵𝗲 𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻: 🔹Templates → slot-filling. 🔹Statistical → n-grams, HMMs. 🔹Neural → Seq2Seq, Transformers. 🔹LLMs → GPT, Claude (SOTA) . Below are 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻s based on use case: 🔹Need predictability → Templates. 🔹Need natural variety → LLM. 🔹Need both → Hybrid (LLM + guardrails).

The difference between a robotic assistant and a delightful one? NLG.