Hey livekit assistant, In our LiveKit voice agent we’re using: • Silero VAD (via the

vad

parameter on Agent) to break the audio into “speech” vs. “silence” segments. • MultilingualModel (an

EOUModelBase

implementation) as the

turn_detection

component on

AgentSession

, which runs LiveKit’s “end of utterance” transformer on the text transcripts to decide when the user’s turn has finished. By default, LiveKit will: • Stream incoming audio through the VAD plugin, emitting “speech” and “silence” events. • After a silence event of at least

min_silence_duration_ms

, invoke the EOU model on the accumulated transcript to confirm that the user really has stopped speaking. • Only once the EOU model signals “end of turn” does the pipeline send the final transcript to the LLM and TTS. Because of that two-step process, we’re seeing 1–1.5 s of “dead air” between the user’s last word and the agent starting its reply—even though our LLM TTFT (~250 ms) and TTS TTFB (~230 ms) are already rock-solid. Questions: • Is my understanding of the LiveKit pipeline correct—i.e. that Silero fires on silence first, and only then does MultilingualModel run on the final transcript? • Are there configurations or best practices to reduce this gap? For example: ◦ Running the EOU model continuously on interim transcripts instead of waiting for a full VAD silence event? ◦ Tuning Silero’s

min_silence_duration_ms

lower (e.g. 200–300 ms) versus relying on MultilingualModel’s own thresholds? ◦ Adjusting MultilingualModel’s

unlikely_threshold

or other parameters to detect end-of-utterance more aggressively? • Does the LiveKit documentation include any examples or recommended settings for achieving sub-700 ms total “user-silent to agent-speaking” latency? Any tips, example settings, or success stories for sub-1 s total response time would be hugely appreciated!

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