How to handle real-time interruptions in your AI voice agent

AI voice agents must distinguish genuine caller interruptions, listener backchannels, and speech-like background noise to maintain natural conversations. Twilio Conversation Relay manages live audio, transcription, text-to-speech, and interruption detection, while an application and its LLM determine responses and must update conversation history to reflect only the portion of an answer the caller actually heard. Configurable controls such as interruptible, interruptSensitivity, ignoreBackchannel, speechTimeout, and welcomeGreetingInterruptible help tailor behavior without major code changes, while Deepgram Flux combines transcription with end-of-turn detection to reduce false interruptions, improve latency, and better handle noise. Effective tuning requires balancing responsiveness against accidental pauses, monitoring interruption events, repeat requests, hang-ups, and escalations, and using human handoffs with transferred context when noise, repetition, or customer needs exceed the AI’s capabilities.

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