Push-to-Talk Audio Getting Cut Off Before Complete Speech Captured** --- Hi LiveKit team, We're experiencing an issue with push-to-talk (PTT) implementation where audio is getting cut off before the user finishes speaking, even though we're using manual turn detection and have implemented delays. ## Current Setup ### Agent Configuration

python session = AgentSession( stt=deepgram.STT( model="nova-3", interim_results=False, # No interim results for PTT endpointing_ms=6000, # 6 second endpointing no_delay=False, # Disable aggressive segmentation punctuate=True, smart_format=True ), tts=deepgram.TTS(model="aura-2-cora-en"), vad=None, # No VAD for PTT turn_detection="manual", # Manual turn detection only allow_interruptions=True, min_interruption_duration=0.1, )

### PTT Flow Implementation Client side (React Native): 1. Button press →

pushToTalk: true

metadata 2. Button release → Wait 10 seconds →

pushToTalk: false

metadata Agent side:

python @ctx.room.on("participant_metadata_changed") def on_metadata_changed(participant, old_metadata, new_metadata): new_ptt = new_meta.get('pushToTalk', False) if new_ptt: # PTT pressed - enable audio session.input.set_audio_enabled(True) else: # PTT released - delayed processing async def delayed_commit(): await asyncio.sleep(2.0) # Wait for transcription session.commit_user_turn(transcript_timeout=5.0) loop.create_task(delayed_commit())

## The Problem ### Test Case User says: "10, 9, 8, 7, 6, 5, 4, 3, 2, 1, zero, postcard" User releases button at: "4" (but continues speaking) Agent hears: Only up to "4" - misses "3, 2, 1, zero, postcard" ### Logs Show Mobile logs:

[PTT] Button released, delaying turn completion signal to capture trailing audio [PTT] 10-second delay complete, now signaling turn completion to agent [PTT] Turn completion signaled to agent

User transcript captured:

"Ten nine eight seven six five four three two one zero describe."

Agent response:

"I heard you count down from 10 to 4, and then it cut off right there"

## Questions ### 1. STT Configuration for PTT With

turn_detection="manual"

, do STT settings like

endpointing_ms

still apply? Could these settings be causing premature audio segmentation even in manual mode? ### 2. Audio Streaming vs Turn Completion When we send

pushToTalk: false

metadata (turn completion signal), does the agent: - A) Process only audio received UP TO that point? - B) Wait for any remaining audio to finish streaming before processing? ### 3. Interim Results Impact Does

interim_results=False

affect how complete audio streams are processed in manual turn detection mode? Would

interim_results=True

help ensure complete audio capture? ### 4. Transcript Timeout Behavior With

session.commit_user_turn(transcript_timeout=5.0)

, does this: - Wait up to 5 seconds for transcription to complete? - Or timeout and process partial transcription after 5 seconds? ### 5. Audio Buffer Flushing Is there a way to ensure all buffered audio is flushed and processed before the agent responds, even with manual turn detection? ## Suspected Root Cause We suspect the issue is that STT processing is cutting off audio streams before completion, possibly due to: -

endpointing_ms=6000

triggering even in manual mode -

interim_results=False

preventing complete stream processing - Audio buffering not flushing completely before turn processing ## Expected Behavior Agent should receive and process the complete audio stream: "10, 9, 8, 7, 6, 5, 4, 3, 2, 1, zero, postcard" even when the PTT button is released at "4". ## Request What's the recommended configuration for PTT with manual turn detection to ensure complete audio capture and processing, especially when users continue speaking briefly after button release? Any guidance on STT settings, timing configurations, or implementation patterns would be greatly appreciated! ## Environment - LiveKit: Latest server version (cloud-hosted) - Agent SDK: Python livekit-agents - Client: React Native with livekit-client - STT: Deepgram nova-3 - Platform: iOS and Android mobile apps Thank you for your excellent support and documentation!

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

mplementing Hybrid PTT: Manual Button Control + Automatic Pause Detection** --- Hi LiveKit team, Following up on our previous PTT audio cutoff discussion, we'd like to implement a hybrid approach that combines manual button control with automatic pause detection. Is this possible with the current LiveKit agents framework? ## Desired Behavior ### Hybrid PTT Logic We want both conditions to be met before committing a turn: 1. User releases PTT button (manual control - user intent) 2. Natural pause detected (e.g., 2 seconds of silence - speech completion) Only when BOTH conditions are true → commit the turn and generate AI response. ### User Experience Goals Scenario 1: User releases button at natural pause - Release button → Already 2s pause → Immediate response ✅ Scenario 2: User releases button mid-sentence - Release button → Continue speaking → 2s pause → Response ✅ - No artificial cutoff because it waits for natural completion Scenario 3: User releases but keeps talking - Release button → Keep speaking → Eventually pause → Response ✅ ## Technical Questions ### 1. Hybrid Turn Detection Is it possible to combine: -

turn_detection="manual"

for button control - AND voice activity/pause detection for natural speech boundaries? Or would we need a different approach? ### 2. Voice Activity Detection with Manual Mode Can we use VAD (Voice Activity Detection) alongside manual turn detection?

python
session = AgentSession(
    _turn_detection_="manual",
    _vad_=silero.VAD.load(),  _# Would this work together?_
    _# ... other settings_
)

### 3. Custom Turn Completion Logic Instead of calling

session.commit_user_turn()

immediately when button is released, could we:

python
_# When button released:_
_if_ button_released:
    _# Wait for natural pause before committing_
    _while_ still_speaking_detected():
        _await_ asyncio.sleep(0.1)

    _# Wait for 2-second pause_
    _await_ wait_for_silence(_duration_=2.0)

    _# Then commit turn_
    session.commit_user_turn(_transcript_timeout_=5.0)

### 4. Speech Activity Monitoring What's the best way to monitor ongoing speech activity in an agent? - Use VAD output directly? - Monitor STT interim results? - Listen for specific audio events? ### 5. Implementation Pattern Do you have any examples or recommended patterns for implementing this type of hybrid PTT behavior in the agents framework? ## Current Implementation Context ### What We Have Working - ✅ Manual PTT with metadata-based control - ✅ Button press/release detection - ✅ Audio enable/disable functionality - ✅ Basic turn commitment with delays ### What We Want to Add - Natural pause detection after button release - Hybrid condition logic (button + pause) - Responsive but complete audio capture ## Use Case Context This is for a mental health reflection app where: - Users need control over when recording starts (privacy/safety) - Natural speech completion is important for therapeutic processing - Avoiding cutoffs is crucial for emotional expression - Responsive interaction maintains conversation flow ## Alternative Approaches Considered Option A: Fixed delays (current) - Too laggy Option B: Immediate turn commit on release - Causes cutoffs Option C: Hybrid approach (requested) - Best UX if possible Any guidance on implementing this hybrid PTT behavior would be incredibly helpful! ## Environment Details - Agent SDK: Python livekit-agents - STT: Deepgram nova-3 - Client: React Native mobile app - Turn detection: Currently manual only Thanks for your continued excellent support!

To help you set up a hybrid PTT system that mixes manual button control with automatic pause detection, could you share a bit more? • Are you thinking of using a particular Voice Activity Detection (VAD) library, or would you like some suggestions? • Do you want this to work with your current STT provider (Deepgram), or are you open to adding other tools? Knowing this will make sure we find the best fit for your setup and what you’re aiming for.

## Our Response to LiveKit ### Current Tech Stack Preferences VAD Library: We're currently using Silero VAD in our live voice agent (agent.py) and it works perfectly:

python
vad=silero.VAD.load()

STT Provider: We'd prefer to stick with Deepgram as it's working well for us:

python
stt=deepgram.STT(_model_="nova-3")

### Current Working Setup (For Reference) Live Voice Agent (No Audio Cutoff Issues):

python
session = AgentSession(
    _stt_=deepgram.STT(_model_="nova-3", _interim_results_=False),
    _tts_=deepgram.TTS(_model_="aura-2-cora-en"),
    _vad_=silero.VAD.load(),                 _#_ :white_check_mark: _This detects natural pauses_
    _turn_detection_=MultilingualModel(),    _#_ :white_check_mark: _Automatic, waits for pauses_
    _allow_interruptions_=False,
    _min_endpointing_delay_=6.0,
    _max_endpointing_delay_=120.0
)

PTT Agent (Audio Cutoff Issues):

python
session = AgentSession(
    _stt_=deepgram.STT(_model_="nova-3", _interim_results_=False),
    _tts_=deepgram.TTS(_model_="aura-2-cora-en"),
    _vad_=None,                  _#_ :x: _No pause detection_
    _turn_detection_="manual",   _#_ :x: _Only button control_
    _allow_interruptions_=True,
    _min_interruption_duration_=0.1,
)

### Desired Hybrid Behavior Both conditions must be met: 1. User releases PTT button (user intent to end) 2. 2-second natural pause detected (speech actually complete) Pseudo-logic:

python
button_released = False
natural_pause_detected = False

_# When button released:_
button_released = True

_# When 2s of silence detected:_
natural_pause_detected = True

_# Only commit turn when BOTH are true:_
_if_ button_released AND natural_pause_detected:
    session.commit_user_turn()

### Questions for Implementation 1. Can we use Silero VAD alongside manual turn detection?

python
session = AgentSession(
    _turn_detection_="manual",
    _vad_=silero.VAD.load(),  _# Would this work for pause detection?_
    _# ..._
)

2. How to access VAD state programmatically? - Monitor VAD output for speech/silence detection - Detect 2-second silence periods - Trigger turn commit only when conditions met 3. Best integration pattern? - Should we handle this in the metadata change handler? - Use VAD events directly? - Monitor audio activity through other LiveKit APIs? ### Use Case Benefits For mental health conversations: - User control ensures privacy and comfort - Natural speech completion captures complete emotional expressions - No rushed speech due to button release pressure - Conversational flow maintained with appropriate pauses We'd love guidance on the best way to implement this hybrid approach with our current Deepgram + Silero stack!

Hey there! Just a quick heads-up: LiveKit doesn’t natively combine Silero VAD with manual turn detection in a single

turn_detection

setting. But don’t worry—you can totally create a hybrid push-to-talk (PTT) setup by mixing manual button control with VAD monitoring right in your app. Here’s a simple way to make it happen: 1. Set `turn_detection="manual"`: This turns off automatic endpointing and puts you in the driver’s seat to decide when a turn ends. 2. Load and use Silero VAD: Keep Silero VAD running in the background to watch for voice activity, even with manual mode on:

from livekit.plugins import silero
session = AgentSession(
    turn_detection="manual",
    vad=silero.VAD.load(),
    # ... other settings
)

3. Keep an eye on VAD events and button presses: Listen for VAD events like

vad_started

and

vad_ended

, and set up RPC or webhook endpoints to catch button press and release signals from your frontend. 4. End the turn based on both: Programmatically wrap up the turn when: Here’s a little example logic:

@ctx.room.local_participant.register_rpc_method("end_turn")
async def on_button_release(data):
    session.input.set_audio_enabled(False)
    session.commit_user_turn()  # Ends turn when button is released

@session.on("vad_ended")
async def on_vad_end(speech_duration):
    if speech_duration > 1.0:  # Only if user actually spoke
        await asyncio.sleep(0.5)  # Wait for a natural pause
        session.commit_user_turn()  # Ends turn on natural pause

◦ The button on the frontend is released. ◦ Silero VAD notices silence longer than your set threshold (say, 2 seconds). This way, you get the best of both worlds—LiveKit’s flexible event system plus manual turn control—to make your PTT feel smooth and natural. If you want, I’d be happy to share a full code example or help you get this set up! Sources: Silero VAD plugin | LiveKit Docs | Turn detection and interruptions | LiveKit Docs | livekit-agents/livekit/agents/voice/agent_session.py | Turn detection and interruptions | LiveKit Docs | Speech & Audio Processing | livekit/livekit_composite | DeepWiki

Validating Hybrid PTT Implementation with Metadata + VAD Events** --- Hi LiveKit team, Thank you for confirming that hybrid PTT (manual + VAD) is possible! Before implementing, we'd like to validate our specific approach since we're using metadata for button control (not RPC) and want to make sure our logic will work correctly. ## Our Planned Implementation ### Agent Configuration (Based on Your Guidance)

python
session = AgentSession(
    _stt_=deepgram.STT(
        _model_="nova-3",
        _interim_results_=True,      _#_ :white_check_mark: _Changed per your recommendation_
        _endpointing_ms_=6000,       _# Keep current setting_
        _no_delay_=False,
        _punctuate_=True,
        _smart_format_=True
    ),
    _tts_=deepgram.TTS(_model_="aura-2-cora-en"),
    _vad_=silero.VAD.load(),         _#_ :white_check_mark: _Added for pause detection_
    _turn_detection_="manual",       _#_ :white_check_mark: _Manual control_
    _allow_interruptions_=True,
    _min_interruption_duration_=0.1,
)

### Hybrid Logic Implementation Our proposed approach using metadata + VAD events:

python
_# Global state tracking_
button_released = False

@ctx.room.on("participant_metadata_changed")
def on_metadata_changed(_participant_, _old_metadata_, _new_metadata_):
    global button_released
    new_meta = json.loads(new_metadata) _if_ new_metadata _else_ {}
    new_ptt = new_meta.get('pushToTalk', False)

    _if_ new_ptt:
        _# Button pressed - start recording_
        session.input.set_audio_enabled(True)
        button_released = False
        <http://logger.info|logger.info>("PTT: Button pressed, audio enabled")
    _else_:
        _# Button released - set flag but don't commit yet_
        button_released = True
        <http://logger.info|logger.info>("PTT: Button released, waiting for natural pause...")

@session.on("vad_ended")
async def on_vad_end(_speech_duration_):
    global button_released

    _# Only commit turn if BOTH conditions are met_
    _if_ button_released and speech_duration > 1.0:
        <http://logger.info|logger.info>(f"PTT: Both conditions met - button released AND {speech_duration}s speech detected")
        _await_ asyncio.sleep(2.0)  _# Wait for 2-second natural pause_
        <http://logger.info|logger.info>("PTT: Committing turn after natural pause")
        session.commit_user_turn(_transcript_timeout_=8.0)

        _# Reset state_
        button_released = False
    _else_:
        logger.debug(f"PTT: VAD ended but conditions not met - button_released: {button_released}, duration: {speech_duration}")

## Validation Questions ### 1. Event Timing and Coordination Will this approach work correctly? Specifically: - Can

vad_ended

events fire while

turn_detection="manual"

? - Will the timing between metadata changes and VAD events coordinate properly? ### 2. STT Processing with Hybrid Approach With our hybrid logic: - Will STT continue processing audio between button release and

vad_ended

? - Should we adjust

transcript_timeout

differently for this approach? ### 3. Edge Cases What happens if: - Button released but user never pauses (keeps talking indefinitely)? - VAD ends but button wasn't released (natural pause during button hold)? - Multiple rapid VAD events during the same turn? ### 4. Performance Considerations - Any performance impact of running VAD alongside manual turn detection? - Memory/CPU considerations for this hybrid approach? ### 5. Fallback Behavior Should we implement a fallback timeout?

python
_# If button released but no VAD silence after X seconds_
async def fallback_commit():
    _await_ asyncio.sleep(10.0)  _# Fallback timeout_
    _if_ button_released:
        logger.warning("PTT: Fallback timeout - committing turn without pause")
        session.commit_user_turn(_transcript_timeout_=8.0)

## Expected Behavior Validation ### Test Case: "Postcard Scenario" User says: "10, 9, 8, 7, 6, 5, 4, 3, 2, 1, zero, postcard" User releases button at: "4" (but continues speaking) Expected with hybrid approach: 1. Button released at "4" →

button_released = True

2. User continues: "3, 2, 1, zero, postcard" 3. User naturally pauses for 2+ seconds 4.

vad_ended

fires → Both conditions met → Turn committed 5. Agent should hear complete message including "postcard" Does this flow align with how VAD events work in practice? ## Implementation Environment - Agent: Python with metadata-based PTT control (not RPC) - Client: React Native mobile app - Current: Working manual PTT but with audio cutoff issues - Goal: Maintain user control while capturing complete speech We're excited to implement this hybrid approach and would love confirmation that our logic aligns with how LiveKit's VAD events actually behave! Thank you for the excellent guidance so far! --- Internal tracking: Validating hybrid PTT approach before implementation

Your proposed hybrid PTT implementation fits nicely with what LiveKit can do. Here are some key points to help you feel confident about your approach: 1. VAD Events with Manual Turn Detection: The

vad_ended

event will still fire even when

turn_detection="manual"

is set. Just keep in mind, these events won’t automatically handle turn-taking—you’ll need to call

session.commit_user_turn()

yourself to end the turn. 2. Event Coordination: VAD events can happen while you’re controlling turns manually, but the exact way they sync up with metadata changes in a hybrid PTT setup isn’t spelled out. Your plan to track

button_released

and wait for

vad_ended

should work well, though I’d recommend giving it a test run to make sure the timing lines up smoothly. 3. Fallback Behavior: Adding a fallback timeout (like 10 seconds) is a smart move to cover cases where there’s no natural pause after the button is released. Your "Postcard Scenario" test should go through just fine with this setup, capturing the full message—including "postcard"—before committing the turn. If you want to chat more or need a detailed code review, just let me know—I’m here to help! Sources: Turn detection and interruptions | LiveKit Docs

but does vad cause waiting based on semanitcs also or just timing here?

Hey there! Just a quick heads-up—standard VADs like Silero VAD mainly look at timing and whether there’s audio to spot pauses in speech. They don’t really dig into the meaning behind what’s being said when figuring out those pauses. If you’re interested in something smarter, LiveKit has some cool options like the transformer-based Turn Detection Model or Semantic VAD (which works with OpenAI’s Realtime API). These tools actually understand the meaning behind the words to better predict when someone’s done talking, helping to avoid those awkward interruptions or cutting people off too soon. Feel free to reach out if you want to dive deeper into these options or need a hand with your current setup—I’m here to help! Sources: OpenAI Realtime API integration guide | LiveKit Docs | Improving voice AI's turn detection with transformers