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When you speak over a voice assistant, two things need to happen: its response must stop, and the conversation history must reflect what you actually heard. OpenAI’s Realtime API documents controls for detecting a new speech turn and cancelling an ongoing response, but the client application still has to stop any audio it is playing and synchronize playback with the conversation state.
Can you interrupt a voice AI while it is talking?
In the documented OpenAI Realtime API, yes. With server or semantic voice activity detection (VAD), the service can detect the start of a new user speech turn while an assistant response is in progress. The interrupt_response setting defaults to true; when enabled, a VAD start event cancels an ongoing response in the default conversation. Set it to false to let that response continue. These are configurable API behaviors, not proof that every voice assistant supports interruption.
The API supports real-time calls over WebRTC, WebSocket, and SIP. Its reference describes the interfaces but does not compare their latency, reliability, or cost, so the transport alone does not establish how quickly a particular application will react.
What happens when you speak over the assistant?
- The session receives your audio. Its turn-detection configuration determines how incoming speech is interpreted.
- The service detects speech start. In server VAD mode, it emits
input_audio_buffer.speech_started. The OpenAI Realtime API reference says, “The client may want to use this event to interrupt audio playback or provide visual feedback to the user.” See OpenAI’s Realtime server events reference. - The response may be cancelled. If
interrupt_responseis enabled, the VAD start cancels the ongoing response in the default conversation. - The client stops playback. The application controls the audio it has queued or is playing. A server cancellation event cannot, by itself, retract sound already rendered by a device; the client must act on the event to stop its output.
- The client reconciles conversation state. If only part of an assistant audio item played, the client can send
conversation.item.truncatewith the item ID and the playback duration. The server responds withconversation.item.truncatedand removes the transcript associated with unheard audio from the conversation context. See the conversation item truncation event documentation. - The next turn can begin. Once the service judges that you have finished, it can create a response automatically if the relevant setting allows it. Otherwise, the application can manage response creation itself.
How does a voice assistant know when you have finished speaking?
The choice of turn detector affects whether the system treats a pause as the end of your turn. The OpenAI reference documents three approaches:
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| Mode | How it detects turn completion | Documented controls | Practical trade-off |
|---|---|---|---|
| Server VAD | Uses audio volume to identify speech and silence to identify its end. | Default silence_duration_ms: 500 ms; default threshold: 0.5; default prefix padding: 300 ms. create_response defaults to true. |
A shorter silence duration can prompt a response sooner, but may cause the assistant to jump in during a brief pause. A higher threshold requires louder speech to activate and may be useful in noisy environments. |
| Semantic VAD | Estimates whether the user has finished speaking, using the audio and context. | Eagerness options low, medium, and high have maximum timeouts of 8, 4, and 2 seconds, respectively. auto is equivalent to medium. |
More waiting can accommodate a speaker who pauses or trails off; greater eagerness can reduce the wait. The reference notes that semantic detection may have higher latency. |
| Manual turn control | The application decides when a turn is complete. | Set turn detection to null; the client triggers responses manually. |
Offers the application direct control, while requiring it to manage turn boundaries and response triggering itself. |
These are API defaults and documented configuration values, not measured performance guarantees. Validate them in the intended acoustic environment. The figures above come from OpenAI’s live Realtime API reference and input audio buffer event documentation; the pages do not state a publication date.
Why must playback and conversation history stay in sync?
A streaming response can exist in conversation state before all of its audio reaches the listener. If the assistant generates a sentence but playback stops halfway through, keeping the full transcript as though it had been heard could mislead later turns. The API’s truncation behavior removes the unheard audio and its associated transcript from server context, aligning that context with client playback. The OpenAI reference describes truncation as a way “to synchronize the server’s understanding of the audio with the client’s playback.”
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In practice, the client needs to track the active assistant audio item and how much has played, stop playback when an interruption is detected, and report the played duration when truncating the item. The documentation describes the event and its purpose; it does not promise a specific buffering method, audible-stop time, or universal solution to timing races.
Does interruptible voice mean the audio system is full duplex?
“Full-duplex voice” is useful here as shorthand for an interaction in which the user can start speaking before the assistant has finished and the assistant can be interrupted. The observable behavior is what matters to the listener: playback may stop, and the next turn can take the new speech into account.
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That behavior alone does not establish full duplex in every strict communications-engineering sense, such as simultaneous independent send-and-receive audio channels. The Realtime API documents real-time communication interfaces and interruption controls; those facts do not certify every application’s audio path or implementation as full duplex.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What is established—and what is not?
- Documented: The Realtime API provides turn-detection options, an interruption control, a speech-start event, and a way to truncate an audio item to match playback.
- Not established by these references: a measured end-to-end interruption time, false-interruption rate, user-satisfaction improvement, intelligence gain, or ranking of WebRTC, WebSocket, and SIP.
For an implementation comparison, focus on how turn boundaries are detected, how the system handles pauses and noise, whether the client stops playback reliably, and how accurately it reports the amount played. The documentation supplies relevant controls but no comparative benchmark for those outcomes.
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