- How interruption handling differs between turn-taking and non turn-taking transcription models.
- How to configure interruption settings via the API.
- How to protect greetings and tune endpointing thresholds.
How it works
Interruption behavior depends on which transcription model your assistant uses.Turn-taking models
Turn-taking models likedeepgram/flux have built-in end-of-turn detection. When you use one of these models, the assistant determines when the caller has finished speaking using the transcription-level settings eot_threshold, eot_timeout_ms, and eager_eot_threshold — configured under transcription.settings. See the Transcription Settings guide for details.
You can still use interruption_settings.enable and interruption_settings.disable_greeting_interruption with turn-taking models, but the start_speaking_plan and transcription_endpointing_plan thresholds are not relevant because the model handles turn detection natively.
Non turn-taking models
For models without built-in turn detection (such asdeepgram/nova-3, deepgram/nova-2, azure/fast, or nvidia/parakeet-v3), the assistant relies on the interruption_settings.start_speaking_plan to decide when to start speaking after the caller stops. This plan uses silence-based endpointing thresholds to detect end of turn.
Configuration
API schema
Set theinterruption_settings object when creating or updating an assistant:
Key fields
Mission Control Portal
You can also configure interruption settings through the Portal:- Navigate to AI > Assistants.
- Select your assistant and click Edit.
- Open the Voice tab.
- Scroll to the Interruption Settings section.
- Toggle interruptions on or off, enable greeting protection, and adjust the start speaking plan thresholds.
Example configurations
Default — allow interruptions
Allow callers to interrupt at any time, including during the greeting. This is the default behavior wheninterruption_settings is omitted.
Protected greeting
Allow interruptions during normal conversation but prevent callers from cutting off the assistant’s initial greeting. Useful for flows where the greeting contains required disclosures or context.Conservative endpointing for non turn-taking models
Use longer silence thresholds to reduce false interruptions in noisy environments or when callers tend to pause mid-sentence. This configuration waits longer before treating silence as end of turn.Use cases
- Call centers with background noise: Increase
wait_secondsand endpointing thresholds to prevent ambient noise from triggering false interruptions. - IVR-style interactions: Keep interruptions enabled so callers can barge in to skip prompts they have already heard.
- Greeting-heavy flows: Enable
disable_greeting_interruptionto ensure callers hear required disclosures, legal notices, or welcome messages before interacting. - Dictation or number entry: Increase
on_number_secondsto give callers time to finish reading out long numbers like account IDs or phone numbers without the assistant cutting in.
Related resources
- Transcription Settings — Configure STT models and end-of-turn detection for turn-taking models like
deepgram/flux. - Create an Assistant API Reference — Full assistant configuration options including
interruption_settings. - End-of-Turn Detection — Lower-level end-of-turn parameters for WebSocket STT streaming.