I understand how important it is to have smooth, uninterrupted conversations during your LiveKit OpenAI coaching sessions. Here are some friendly strategies that can help prevent the AI from interrupting: • Turn Detection Model: You might find it helpful to use a context-aware turn detection model. This approach looks at the conversation history and meaning behind the words to better understand when someone is still speaking, reducing those awkward interruptions. • Adjust VAD Sensitivity: Another tip is to tweak the silence threshold by adjusting the

min_endpointing_delay

parameter. For instance, setting it to 1.0 seconds allows the AI to wait a bit longer before jumping in, giving you more breathing room. • Push-to-Talk: You could also consider a push-to-talk setup, which lets users decide exactly when to speak. This way, the AI responds only after you’ve finished, giving you full control. • Behavioral Guidance: It’s helpful to include a gentle prompt at the start, like: "Please speak in full thoughts and pause for a second when you're done so I can respond." This encourages a respectful flow of conversation. These little tweaks can really make your interactions feel more natural and respectful. If you'd like, I’m here to walk you through any of these steps in more detail—just let me know! Sources: packages/basics/src/uninterruptable.ts | basics/interrupts_user.py | livekit-agents/livekit/agents/voice/speech_handle.py | Improving voice AI's turn detection with transformers | Turn detection and interruptions | LiveKit Docs