OpenBMB / OpenBMB/MiniCPM-o-Demo
TTFS on full duplex
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 386
- Forks
- 81
- Avg merge
- 1h 59m
- Merged PRs (30d)
- 3
Description
Hello, thanks a ton for making this. Has a lot of potential. The TTFS being like 1.5 seconds negates the whole idea of full-duplex though. Any way to improve that? I was not getting much lower than that on a 5090. Should I try on a different GPU?
Also, I noticed it responded a bit faster when I spoke while it was in the middle of speaking. Could there be a way to keep it in that mode, but have it just finish talking and wait, without triggering end-of-turn? This would avoid the TTFS start up time.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No files, tests, or code entry points are identified in the issue. Start by locating the full-duplex inference and end-of-turn handling paths, then measure TTFS on the reported hardware and reproduce the speaking-while-speaking behavior. Done should include a defined latency target and verified behavior that avoids unintended end-of-turn triggering.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- ai, audio-video-rtc, performance
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100