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DynamicEndpointing: one long silence between user utterances inflates min_delay for the rest of the session

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Dal 11/10/2026.

  • #7750 di @NabiBukhsh-AI — aperta

Valutazione

Difficoltà
3/5
Tempo stimato
Mezza giornata
Idoneità per principianti
35/100
Tipo di issue
Bug
Chiarezza
Specificata chiaramente
Stato di attività
Ferma
Stack tecnologico
python

Direzione di ricerca

Start with voice/endpointing.py and inspect DynamicEndpointing.on_end_of_speech, especially the between-utterance pause update. Add coverage for a pause longer than max_delay and confirm it does not raise the learned min_delay; retain the existing behavior for shorter pauses. An open pull request (#7750) is already linked.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Environment

  • livekit-agents 1.8.5 (voice/endpointing.py is identical in 1.8.6 and on main)
  • turn_handling={"endpointing": {"mode": "dynamic", "min_delay": 0.3, "max_delay": 2.5}} (alpha 0.9)

What happens

DynamicEndpointing learns min_delay from the pause between two user utterances with no agent speech in between. That pause goes into ExpFilter.apply() unbounded, and only the filtered result is clamped to max_delay. One long silence, such as a user waiting for a reply that never came because STT dropped a short "yes", lifts the learned floor far above anything a mid-turn pause would justify. Every later turn of the session then waits that long before committing.

Repro

from livekit.agents.voice.endpointing import DynamicEndpointing

ep = DynamicEndpointing(min_delay=0.3, max_delay=2.5, alpha=0.9)
ep.on_start_of_speech(0.0)
ep.on_end_of_speech(0.3)     # a short "yes" that STT drops: no reply follows
ep.on_start_of_speech(15.5)  # the user speaks again after 15.2 s of silence
ep.on_end_of_speech(16.7)

assert ep.min_delay <= 1.0, ep.min_delay  # AssertionError: 1.79 (0.9*0.3 + 0.1*15.2)

On a real phone call this produced exactly that: end_of_utterance_delay went from 0.52 s to 1.79 s and stayed between 1.67 s and 2.13 s for the rest of the call (18 turns). Replaying the user/agent state events of 84 recorded sessions through DynamicEndpointing gave 51 of 624 user turns committed on a floor above 1 s, across 6 sessions, all of them phone calls.

Proposed fix

min_delay exists to cover pauses inside a user's turn. A pause longer than max_delay can never be covered, because the floor is clamped to max_delay. Learning from such a pause only adds latency. In the "pause between utterances" branch of on_end_of_speech, skip the update when pause > self.max_delay:

if (
    (pause := self.between_utterance_delay) > 0
    and pause <= self.max_delay
    and self._agent_speech_ended_at is None
    and self._agent_speech_started_at is None
):

Clamping the sample to max_delay instead still moves the floor by (1 - alpha) * max_delay (0.22 s) per long silence. Over the same 84 sessions the highest floor was 0.94 s with clamping and 0.62 s with the skip.

We currently ship this as a subclass injected through agent_activity.create_endpointing. We would be glad to drop it once this is fixed upstream, and can open a PR if that helps.

Lingua principale
Python
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PR unite (30g)
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