Why full duplex matters for real-time voice AI agents
An English conversation coach is trying to automate their own coaching work with a voice AI app. The current app uses a : speech is turned into text, an LLM creates the answer, and the answer is spoken back to the learner. That setup works, but it still feels like turn-taking instead of a natural conversation.
The LLM’s conversation skill and memory are good enough to be useful, but latency makes the feel less human. is also hard to achieve because the system waits for each step to finish before responding. Full duplex models look promising because they can listen and speak more like a person in a live conversation.
Demos from Moshi and NVIDIA made this direction feel realistic for replacing a human conversation coach in the future.
Key points
- The use case is an AI app that replaces an English conversation coach.
- A makes feel turn-based and less natural.
- The LLM’s conversation ability and memory are not the main problem.
- Latency and weak are the biggest blockers.
- Full duplex could make feel more like live human conversation.