What’s generally a good min_endpointing_delay folk...
# ask-ai
m
What’s generally a good min_endpointing_delay folks use for their telephony VAD systems?
t
Thanks for reaching out, Alexander. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.
You're asking about a good value for
min_endpointing_delay
in telephony VAD — a common default is 500 ms (0.5 s). • 500 ms balances responsiveness with avoiding premature cutoffs. • Shorter values (200–300 ms) feel more responsive but risk interrupting speakers. • Longer values reduce false endpoints but can make turn-taking feel sluggish. • Some setups also use a
max_endpointing_delay
(e.g., ~6 s) to handle low-confidence endings. Would you like help tuning this for a specific use case (call length, noise level, or model confidence thresholds)? Sources: Improving voice AI's turn detection with transformers | How does end-of-utterance detection work in conversations? | Agents Framework | livekit/livekit_composite | DeepWiki | examples/voice_agents | livekit/livekit_composite | DeepWiki | examples/frontdesk | livekit/livekit_composite | DeepWiki
m
What’s max endpointing delay?
t
You're asking what "max_endpointing_delay" means. • Definition: It's the maximum wait time after detected silence before forcibly ending a speaker's turn when the VAD has low confidence that the speaker has finished. • Typical value: Commonly around 6.0 seconds in telephony setups. • Behavior: It prevents excessively long waits when minor noises or low-confidence silence extend turn detection; shorter values close the turn faster but risk cutting off trailing speech, longer values allow more natural pauses but delay turn transitions. Would you like guidance picking
max_endpointing_delay
for a noisy environment or short-interaction use case?