what is the best min_interruption_words for the most human like conversation quality

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

what do you recommend for English speech when im using the BVC and EOU for background voice cancellation and turn taking?

For English speech using Background Voice Cancellation (BVC) and End of Utterance (EOU) detection, I’d warmly suggest setting

min_interruption_words

to 2. This setting beautifully balances being responsive while gently filtering out unintended interruptions, helping conversations flow naturally. Here’s a little breakdown to help you understand: • 1 Word: Very quick to respond but might catch short phrases like "Hey" or "Wait" as interruptions. • 2 Words: A great middle ground that filters out single-word interruptions but still catches natural phrases like "Go on" or "Yes, please." • 3 Words: Best for more structured chats where interruptions should be more intentional, reducing false alarms even more. When you pair this with BVC to minimize background noise and EOU for smart turn detection,

min_interruption_words=2

really helps create smooth, human-like interactions. If you notice too many false interruptions, gently nudging it up to 3 might help. Or if you want things to feel snappier, lowering it to 1 could do the trick. And of course, I’m here if you’d like a hand adjusting other settings like

min_interruption_duration

or tailoring configurations to fit your unique needs. Sources: livekit-plugins/livekit-plugins-turn-detector/livekit/plugins/turn_detector... | Improving voice AI's turn detection with transformers | How does end-of-utterance detection work in conversations? | Turn detection and interruptions | LiveKit Docs

best min_endpointing_delay when using preemptive_generation?

Thanks for reaching out! The recommended

min_endpointing_delay

setting when using

preemptive_generation

is 0.5 seconds. This default value usually works really well, striking a nice balance between responsiveness and accurate turn detection. If you happen to notice premature turn detection or if you're working in environments with longer pauses, you might want to try increasing it to 0.75 seconds. This small tweak can often help reduce false turn endings while keeping the interaction feeling natural. Feel free to reach out if you'd like any more help or tips on fine-tuning this for your specific needs—I’m here to support you! Sources: ivr-nagivator/README.mdoc | VoicePipelineAgent | LiveKit Docs | Turn detection and interruptions | LiveKit Docs | Speech & Audio Processing | livekit/livekit_composite | DeepWiki | livekit-agents/livekit/agents/voice/agent.py

what's a good min_interruption_duration if I want short interjections to be ignored?

To help you smoothly handle short interjections, a great starting point is the

min_interruption_duration

set to 0.5 seconds, which is actually the default. This way, little utterances like "uh" or "hmm" won’t be mistaken as interruptions, keeping your conversations feeling natural and easy. If you'd like to get even more precise, you can pair this with

min_interruption_words

. This setting makes sure that an interruption is only recognized when there's both a minimum speech duration and a certain number of transcribed words. Feel free to reach out if you'd like some help tweaking these settings to fit your unique needs—I’m here to assist! Sources: Turn detection and interruptions | LiveKit Docs

even when i set min_interruption_duration really high it still interrupts on short interjectiosn

I understand that even with a high

min_interruption_duration

, interruptions might still happen on short interjections if Speech-to-Text (STT) interim transcripts trigger them. Don’t worry—we can fine-tune a few settings to help with this: 1. Set `min_interruption_words`: This requires a minimum number of transcribed words (like 3) so that only meaningful utterances cause interruptions. 2. Adjust `min_interruption_duration`: Keeping this high (around 0.8–1.0 seconds) helps filter out brief voice activity. 3. Modify `min_endpointing_delay`: Setting this to 0.5 seconds or more prevents interruptions during natural pauses. Here’s an example to illustrate:

session = AgentSession(
    min_interruption_duration=0.8,  # VAD-based minimum speech duration
    min_interruption_words=3,       # STT-based minimum word count
    min_endpointing_delay=0.5,      # Minimum silence to end turn
    # ... other parameters
)

This setup helps ensure interruptions only happen when there’s enough speech duration and meaningful content, which should reduce those false positives from short interjections. If you’d like, I’m here to help you adjust these settings further or answer any questions you have! Sources: livekit-agents/livekit/agents/voice/speech_handle.py | VoicePipelineAgent | LiveKit Docs | Turn detection and interruptions | LiveKit Docs