do you have a silence detection?

Thanks for reaching out, Joshua. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.

im in a dilemma, so whats happeneing is that using silero VAD is fine we are having nice results. but using gemini realtime results in the model not detecting the user speaking state and its compltely ignorring that and always pushing responses even if the user is speaking. if the setting is at 6s through user speech we see silence detection being said. if i use both user speech gets cut - it does not make it to the LLM only so users end up repeating themself and its a bad experience. disabling the server side vad also causes some really strange things to happen with start speech sensitivity and end speech at high lots of the audio we see was getting chopped, and also at low all the background causes interruptions and its a really bad experience overall

Thanks — that sounds frustrating. You’re describing two problems: Gemini Realtime’s server-side turn detection is ignoring user speech (responding while the user is still speaking), and when you try to combine Silero VAD with Gemini the user audio gets cut and never reaches the LLM. Quick summary of what’s happening and the root cause: • Gemini Realtime has built‑in automatic activity detection by default. If both that and Silero (client-side) are active, they can race and produce premature end-of-turn signals, chopped audio, or ignored speech. • Disabling Gemini’s detection requires a compatible STT/turn-detection pipeline (otherwise endpointing or transcription won’t work), and mis-tuned thresholds can cause background noise to trigger or real speech to be cut. What you can do next (pick one path): 1) Use Gemini server-side detection only (simpler) • Disable Silero VAD on the client and let Gemini handle turn detection. • Tune Gemini endpointing: reduce or increase

silence_duration_ms

and

threshold

to find the sweet spot (shorter = faster responses but more chance of cuts; higher threshold = ignore background noise). 2) Use client-side Silero + turn detector only (more control) • Disable Gemini’s

automatic_activity_detection

. • Keep or add a streaming STT for transcription-based endpointing (required when disabling Gemini VAD). • Tune Silero parameters: increase

min_silence_duration

(to avoid chopping) and raise activation/threshold to reduce background triggers. 3) If you must combine (not recommended) • Ensure clear handoff: disable automatic endpointing on one side and use the other exclusively for signaling turn starts/stops. • Add conservative endpoint delays (increase

min_endpointing_delay

) to avoid race conditions. Tuning pointers: • Increase

min_endpointing_delay

(default 0.5s) if responses interrupt ongoing speech. • Increase VAD activation threshold to reduce background-triggered endpoints. • For chopped speech, confirm only one VAD/turn-detector is actively signaling end-of-turn. To help you quickly, can you share: • Your AgentSession (or equivalent) config showing the

realtime_input_config

/

automatic_activity_detection

and whether you’re using an STT (which model)? • Whether Silero runs client-side (JS) or server-side, and the specific Silero parameters you’ve set (e.g.,

min_silence_duration

, activation threshold)? Send those and I’ll suggest exact config changes and a short code patch you can apply. Sources: Gemini Live API plugin | LiveKit Documentation | How to detect and handle silence during calls | Azure OpenAI Realtime API and LiveKit | LiveKit Documentation | xAI Grok Voice Agent API plugin | LiveKit Documentation | Turns overview | LiveKit Documentation, with interactive elements

is there no way for me to enable it in some way? google_realtime_llm (map) language "en-US" (string) model "gemini-live-2.5-flash-native-audio" (string) realtime_input_config (map) automatic_activity_detection (map) disabled false (boolean) end_of_speech_sensitivity "END_SENSITIVITY_LOW" (string) prefix_padding_ms 200 (int64) silence_duration_ms 600 (int64) start_of_speech_sensitivity "START_SENSITIVITY_LOW" (s silence_detection_config (map) check_interval_sec 1 (double) enabled true (boolean) max_silence_checks 3 (int64) min_time_between_prompts 20 (int64) silence_threshold_sec 20

Thanks — I can work with that config. You can absolutely enable and tune Gemini’s server-side silence detection; your snippet already shows it’s enabled. The main issue is coordinating it with Silero so they don't race. What I recommend based on your current settings: • Keep

automatic_activity_detection.disabled = false

(server VAD enabled) if you want Gemini to be the authoritative turn detector. • Increase

prefix_padding_ms

from 200ms if responses are cutting off user starts; try 400–600ms. • Your

silence_duration_ms = 600

is short (0.6s). Increase it to 800–1200 ms to avoid chopping mid-utterance. •

end_of_speech_sensitivity = "END_SENSITIVITY_LOW"

is conservative; if the model still ends too early, try

MEDIUM

to make end detection less aggressive. •

start_of_speech_sensitivity = "START_SENSITIVITY_LOW"

plus a short

prefix_padding_ms

can cause false starts; try

MEDIUM

if it misses user starts. • For `silence_detection_config`: ◦

check_interval_sec = 1

and

max_silence_checks = 3

mean up to ~3s before a silence action — that’s okay; lower

max_silence_checks

to 2 if you want faster cuts, increase to 4–5 for more tolerance. ◦

silence_threshold_sec = 20

is long (20s) — if you want earlier inactivity detection, reduce it to something like 60–120s (or keep 20s if intentional). Critical: disable Silero VAD signaling to Gemini (or disable Gemini automatic detection) — do not have both actively sending end-of-speech signals. Mixing them causes the exact race you described. Choose one: • If you keep Gemini server-side detection: stop client-side Silero from emitting end-of-turn events to the server. • If you prefer Silero: set

automatic_activity_detection.disabled = true

and ensure you have a streaming STT feeding the turn-detection pipeline. Quick next step for me to give exact values or a code patch: • Do you want Gemini to be authoritative (server-side) or Silero (client-side)? • Are you using streaming STT alongside Silero? If so, which STT model?, with interactive elements

but its still really buggy, what exactly is that padding doing?

Good question — I’ll explain exactly what

prefix_padding_ms

does and how it affects the behavior you’re seeing. What

prefix_padding_ms

does • It adds a short amount of audio (in milliseconds) from before the detected start-of-speech to the segment sent to the model. Think of it as “give me a little bit of audio that happened just before the model thought the user started speaking.” • Purpose: it helps capture the very start of a user utterance (soft onsets, breath, clipped phonemes) so the model doesn’t miss the beginning of words when start detection is imperfect. How that affects behavior you’re seeing • If it’s too small (e.g., 200 ms) and your start detector underestimates the true start, the model can miss initial phonemes → user speech sounds cut. • If it’s larger (400–600 ms), you’re more likely to include the true start even when the detector lags, reducing chop at the beginning. • But larger padding increases latency (you send slightly more audio) and can increase the chance of including background noise or previous speaker audio if turn detection is fuzzy. • If client-side Silero and Gemini both signal starts, padding can mask or worsen races: each system may assume different boundaries and include overlapping audio. Tuning recommendations • If speech is getting cut at the start: raise

prefix_padding_ms

to 400–600 ms and test. That usually recovers missing initial phonemes. • If you see extra background or overlap with other speakers: lower padding (200–300 ms) and instead tune

start_of_speech_sensitivity

to be less aggressive. • Combine adjustments: ◦ Increase

prefix_padding_ms

to 400–600 ms ◦ Set

silence_duration_ms

to 800–1200 ms (reduce mid-utterance chopping) ◦ Use

START_SENSITIVITY_MEDIUM

(if start misses) or

LOW

(if false starts) ◦ Ensure only one source (Gemini OR Silero) is authoritative for start/end signals. • Run quick A/B tests with short prompts and background noise levels representative of your users to find the sweet spot. If you want, tell me which padding value you want to try and whether you want a suggested full config (start/end sensitivity, silence_duration_ms, and endpoint delays) to paste into your session — I’ll provide a precise set to test. , with interactive elements

how do i make sure its detecting user speech? I removed silero vad but its still like doing something really strange right. I'm speaking and speaking but the generation just suddently comes up 8s later mid speech, why is that?

Thanks — I hear your frustration. You removed Silero but Gemini is still starting generation mid-speech ~8s later. Here’s why that happens and exactly what to check and tweak right now. Why Gemini can start mid-speech • Gemini’s server-side automatic activity detection still decides when an utterance ended and when to trigger generation. If it misclassifies pauses as end-of-speech, it will finalize the segment and generate, even while you keep speaking. • Two timing factors cause delayed/mid-speech generation: ◦ endpointing delays (the detector waits up to

max_endpointing_delay

/ multiple silence checks before committing), ◦ or a late end-of-speech detection combined with a large buffering window so the model begins generating on a chunk that contains ongoing speech. • Network/transcription buffering or an STT pipeline can add extra lag if you use streaming STT before the LLM. Immediate checks (do these first) 1. Confirm

automatic_activity_detection.disabled = false

(you said removed Silero but server detection still on — that’s fine if intended). 2. Check

silence_duration_ms

— with 600 ms, short pauses may be treated as ends; increasing to 800–1200 ms reduces premature endpoints. 3. Check

prefix_padding_ms

— low value (200 ms) can cause the model to miss starts; increase to 400–600 ms to include the true start. 4. Inspect `silence_detection_config`: ◦

check_interval_sec

and

max_silence_checks

determine how long the detector waits before declaring silence. With check_interval=1 and max_silence_checks=3 you can get ~3s of wait; combine with other buffering for ~8s visible delay. Increase

max_silence_checks

to be more tolerant (4–6) or decrease it to make decisions faster—choose depending on whether you want more tolerance or responsiveness. 1. Verify you don’t have an additional STT/transcription buffering layer delaying events. If you stream STT into the LLM, that pipeline can add seconds before the LLM is notified. Concrete tuning to try now • Set: ◦

prefix_padding_ms = 500

◦

silence_duration_ms = 1000

◦

start_of_speech_sensitivity = "START_SENSITIVITY_MEDIUM"

◦

end_of_speech_sensitivity = "END_SENSITIVITY_MEDIUM"

◦

silence_detection_config.check_interval_sec = 1

◦

silence_detection_config.max_silence_checks = 4

• Purpose: include initial audio, avoid mid-utterance chop, and reduce short-pause false endpoints while keeping latency reasonable. If that still produces an ~8s lag, check these next • Is there a streaming STT model active? If yes, how long is its processing/latency? • Are you batching audio or using a long buffer before sending to Gemini? • Are you seeing repeated endpoint events in logs? (Look for multiple end_of_speech events or late timestamps.) Can you share: • Whether you have streaming STT enabled (which model), and • Any server logs showing timestamped start/end events (or a short trace of when you start speaking vs when the model received end-of-speech)? Send that and I’ll read the timestamps and give a precise config and any quick fixes (e.g., disable STT buffering, tweak checks, or move to client-side detection). , with interactive elements

the silence interval checks or whatever i put at 20 cause its a bit too irritating, it was at 6. There must be some setting as this is consistent behavior. Anytime i speak for 6-8s it interrupts me with are you still there while also simultaneously picking up everything that is said, how is this possbile, is this my silence detection code? Im relying it to pass events of user speaking and agent listening at thsi time instead its passing user listening always i think

Thanks — I hear you. That repeated “are you still there” after 6–8s is almost certainly coming from an inactivity/silence-check path (either Gemini’s

silence_detection_config

or your own timeout handler), not random audio capture. Here’s how to pinpoint and fix it. What’s happening • With

check_interval_sec = 1

and

max_silence_checks = N

, the system can trigger an inactivity action after ~N seconds of perceived silence. If N is 6 (or you set overall silence threshold ~20s elsewhere), that maps to the 6–8s behavior you see. • If the detector mislabels brief pauses as “silence” while you keep speaking, it will send an end-of-speech/inactivity event and the model will respond mid-speech. That event can also flip your UX state (user speaking → agent listening) incorrectly. Immediate checks (do these now) 1. Confirm which component emits the “are you still there” prompt: ◦ Is it your app logic listening to silence events, or a message generated by Gemini/LiveKit? Check the source of that prompt in logs. 1. Share your current

silence_detection_config

(you mentioned changing to 20 and it was 6 before) and any app-level inactivity timers. 2. Inspect logs for timestamps of: ◦ user audio start ◦

end_of_speech

or

inactivity

events ◦ model generation start This will show whether the silence checks or an upstream buffer produced the trigger. Quick fixes to try • Increase tolerance: ◦ Set

silence_detection_config.max_silence_checks = 8–12

(so short pauses don’t trigger) OR increase

silence_threshold_sec

if that’s the controlling value. • Make endpointing conservative: ◦

silence_duration_ms = 1000

(1s) ◦

prefix_padding_ms = 500

◦

start_of_speech_sensitivity = "MEDIUM"

◦

end_of_speech_sensitivity = "MEDIUM"

• Prevent race with your app: ◦ If your app also times out and sends “are you still there,” disable that while tuning server-side settings. • Add debounce logic in your handler: ◦ When you receive an end-of-speech/inactivity event, wait ~500–800ms to confirm no new audio frames before switching state or prompting. If you want a precise patch, please tell me: • The exact current values for

silence_detection_config

(check_interval_sec, max_silence_checks, silence_threshold_sec). • Whether the “are you still there” prompt is generated by your code or by Gemini/LiveKit. • Whether any streaming STT or buffering layer sits between audio input and Gemini. Send those and I’ll return a targeted config and a short code snippet to debounce/confirm inactivity so you stop getting mid-speech interruptions. , with interactive elements

silence_detection_config (map) check_interval_sec 1 (double) enabled true (boolean) max_silence_checks 3 (int64) min_time_between_prompts 20 (int64) silence_threshold_sec 20

Thanks — that helps. I’ll be concise and actionable. Why you see the 6–8s interruption • Your

silence_detection_config

is enabled with

check_interval_sec = 1

and

max_silence_checks = 3

. That means the silence monitor can declare inactivity after roughly 3 checks ≈ 3 seconds of perceived silence. Combined with other endpointing delays/buffering (STT or LLM buffering,

silence_duration_ms

, and any application timers), that can produce the ~6–8s behavior you described. •

min_time_between_prompts = 20

prevents repeated prompts too quickly, but does not prevent the first premature “are you still there” from firing. • If the silence detector misclassifies short pauses while you continue speaking, it emits an end/inactivity event which flips your app state to “agent listening” and triggers the prompt mid-speech. What to check now (quick) 1. Confirm whether the “are you still there” prompt is generated by: ◦ your app logic (an inactivity handler), or ◦ Gemini/LiveKit (a generated response). Check logs to see which component created it and the exact event/timestamp that preceded the prompt. 1. Confirm whether a streaming STT or any audio buffering sits between input → Gemini, and the per-request latency of that STT. Immediate changes to reduce mid-speech interruptions (apply and test) • Make endpointing more tolerant to brief pauses: ◦ Increase

max_silence_checks

from 3 → 6–10. ◦ Keep

check_interval_sec = 1

(or raise to 1.5s if you want fewer checks per second). ◦ Or increase

silence_threshold_sec

to a larger value (e.g., 30–60s) if you want long inactivity windows for prompts. • Make turn endpointing less aggressive: ◦

silence_duration_ms = 800–1200

◦

prefix_padding_ms = 400–600

◦

start_of_speech_sensitivity = START_SENSITIVITY_MEDIUM

◦

end_of_speech_sensitivity = END_SENSITIVITY_MEDIUM

• Add debounce/confirm logic in your app: ◦ When you receive an inactivity/end event, wait 500–800 ms and verify no new audio frames before switching state or prompting. Why these help • Increasing

max_silence_checks

avoids declaring silence on brief pauses. • Raising

silence_duration_ms

and

prefix_padding_ms

reduces chop at starts and middle-of-speech endpointing. • Debounce prevents a single misclassified frame from flipping UX state. If you prefer a single, concrete config to paste and test, try this: •

silence_detection_config.check_interval_sec = 1

•

silence_detection_config.max_silence_checks = 8

•

silence_detection_config.min_time_between_prompts = 20

(keep) •

silence_detection_config.silence_threshold_sec = 60

•

realtime_input_config.automatic_activity_detection.disabled = false

•

realtime_input_config.automatic_activity_detection.silence_duration_ms = 1000

•

realtime_input_config.prefix_padding_ms = 500

•

realtime_input_config.start_of_speech_sensitivity = "START_SENSITIVITY_MEDIUM"

•

realtime_input_config.end_of_speech_sensitivity = "END_SENSITIVITY_MEDIUM"

Next steps I can take for you • If you share logs showing timestamps for: audio start, end_of_speech/inactivity event, and model generation start, I’ll pinpoint which layer is emitting the event and give an exact minimal patch. • Or tell me whether the “are you still there” text is created by your app or by Gemini/LiveKit and whether you have streaming STT; I’ll return a tailored fix. Sources: How to detect and handle silence during calls | Silero VAD plugin | LiveKit Documentation | Turns overview | LiveKit Documentation | Gemini Live API plugin | LiveKit Documentation | OpenAI Realtime API plugin guide | LiveKit Documentation, with interactive elements