A voice assistant that handles barge-in reliably must do two things at once: stop audio that the user is interrupting and correct the conversation history so unheard speech is not treated as heard. It must also preserve the application task state behind the conversation, allowing a user to ask a follow-up such as “What was that last thing?” or continue a form, search, or workflow without starting over.
For a browser application, a stateful speech-to-speech Realtime session is the most direct starting point. Use WebRTC when you want the platform to manage the media path and output buffering; use WebSocket when you need tighter client-side control and are prepared to implement playback cancellation and truncation yourself. The design below separates those transport details from the durable conversation and task state that make follow-ups coherent.
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What interruption handling actually requires
“Stop talking when I start talking” is only the visible part of barge-in. A correct implementation has four coordinated actions:
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- Detect the new user speech. This can come from server-side voice activity detection (VAD), semantic VAD, or an explicit application boundary.
- Cancel the active response. The model should not continue generating an answer that the user has already taken over.
- Stop audio that has not been heard. Clear or halt queued playback according to the transport you selected.
- Reconcile history. Retain only the portion of assistant audio that was actually played. Otherwise the next turn may refer to words the user never heard.
The fourth action is the one many prototypes miss. Interruption is a conversation-state transition, not merely a media-player event. After cancellation, process the new user turn against the corrected history and the still-valid application task state.
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Choose the interaction architecture
There are two practical patterns. Your choice should follow the latency, control, and reuse requirements of the product rather than a claim that one pattern is universally better.
| Architecture | Best fit | What the platform can handle | What your application must own |
|---|---|---|---|
| Stateful speech-to-speech Realtime session | New voice agents that need natural turn taking, barge-in, session state, and realtime tool use | Audio turns, live conversation state, response cancellation, and transport-specific output buffering | Session setup, application task state, tool authorization, UI state, and recovery policy |
| Chained speech-to-text, text agent, and text-to-speech | Products that already have separate transcription, text-agent, or speech services, or need independent control of each stage | Whichever stages you explicitly integrate | More of the turn boundaries, buffering, cancellation, timing, and state handoffs between stages |
The Realtime guide describes this speech-to-speech path as a starting point for agents that need barge-in, low first-audio latency, natural turn taking, and realtime tool use. A chained design can still be the right choice when an existing text agent is the core of your product or when independent control of transcription and synthesis matters more than a single live session.
Browser architecture and trust boundaries
Use a trusted server for credentials
The browser should not contain a long-lived project API key. Your server creates an ephemeral client credential through the documented session flow, and the browser uses that short-lived credential to establish its live connection. Keep the project key in the server environment and apply your normal authentication, authorization, rate limiting, and origin checks before issuing a client credential.
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Meet the browser prerequisites
- A server runtime for the session-creation example.
- A project API key stored on the trusted server.
- Microphone permission in the browser.
- HTTPS in deployment, or
localhostduring local development.
A dedicated USB microphone is optional for desktop prototyping; the documented browser flow requires microphone access, not a particular microphone model.
Prefer WebRTC for a browser media path
The browser WebRTC guide recommends WebRTC rather than WebSocket for more consistent performance. In this arrangement, the browser negotiates a media track for microphone and assistant audio, while a data channel carries session events. The server remains responsible for issuing the ephemeral credential; the browser never needs the permanent key.
Choose WebSocket only with explicit ownership
WebSocket provides more direct control, but the application must capture audio, send it, play returned audio, stop playback on interruption, and reconcile truncated assistant output. This is useful when you need a custom audio pipeline or non-browser transport, but it creates more places for state to diverge.
Model the assistant as three related state machines
Keep these states separate even though they interact:
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Live conversation state
This is the current session history: user turns, assistant output, tool calls, and the portion of each response that was delivered. It supports immediate references such as “repeat the last step” or “what did you just say?”
Playback state
Track whether assistant audio is idle, playing, queued, stopping, or already truncated. For WebSocket, also track the playback cursor or equivalent amount of audio delivered so you can tell the session which output was heard. For WebRTC and SIP, the server manages the output audio buffer and automatic truncation behavior described in the Realtime conversations documentation.
Application task state
Store durable facts needed to continue work: the selected account, search filters, form fields already confirmed, a booking draft, or the current step in a workflow. This state should survive a response cancellation and, when appropriate, a later voice session. It is not a substitute for conversation history; it is the structured representation of work that must not be lost when a user interrupts.
Pick a turn-detection strategy deliberately
Turn boundaries determine when the assistant begins responding. The Agents SDK describes three broad choices:
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|---|---|---|---|
| Server VAD | Starts and ends turns from audio thresholds and timing | You want automatic hands-free turn detection with explicit controls | Threshold, prefix padding, silence duration, and idle timeout must suit your microphones and environment |
| Semantic VAD | Uses the apparent completeness of the speaker’s thought and may wait longer when speech sounds unfinished | You prefer more natural conversational boundaries | Pauses and unfinished phrases need testing with real speakers |
| Manual boundaries | Your application decides when a turn starts and ends | You need deterministic push-to-talk or custom interaction rules | You must provide the boundary controls and prevent accidental early submission |
There is no universally correct threshold or silence duration. Tune with representative voices, short pauses, long pauses, background noise, media playback, and people who interrupt mid-sentence. A setting that feels responsive in a quiet development room can cut off a user in a noisy kitchen or wait too long after a concise command.
Build the browser assistant step by step
1. Create a session endpoint
Implement a server route that authenticates your application user, creates the ephemeral client credential using the current Realtime session flow, and returns only the short-lived value and the session information the browser needs. Do not send the project API key to JavaScript, HTML, browser storage, or a mobile bundle.
2. Establish the media connection
- Serve the application from HTTPS or
localhost. - Request microphone permission only when the user starts the voice feature, and explain why access is needed.
- Fetch the ephemeral credential from your server.
- Connect using WebRTC for a browser media track, or open the WebSocket route if your application intentionally owns capture and playback.
- Subscribe to session events through the negotiated data channel or WebSocket.
Keep connection setup separate from task initialization. A reconnect should be able to restore the task state without replaying every prior audio sample.
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3. Keep explicit local status
At minimum, expose states equivalent to idle, listening, assistant_playing, interrupting, processing, error, and reconnecting. The UI can then show whether the assistant is listening, has stopped because the user took the turn, or is waiting for a clarification. Do not infer these states solely from a button label; update them from audio and session events.
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Start with the VAD mode that matches your interaction design. For server VAD, expose configuration for threshold, prefix padding, silence duration, and idle timeout rather than burying values in client code. For semantic VAD, test unfinished sentences and deliberate pauses. For manual boundaries, make the start and stop controls obvious and accessible.
5. Treat barge-in as an atomic transition
The transition should be serialized so a late playback callback cannot restart audio after the user has taken the turn:
onUserSpeechStart() {
state = "interrupting";
cancelActiveAssistantResponse();
stopOrClearAssistantPlayback();
reconcileAssistantHistoryWithAudioActuallyPlayed();
state = "listening";
}
onUserTurnComplete(userInput) {
appendUserTurn(userInput);
state = "processing";
requestNextResponse();
}The function names above are illustrative boundaries in your own code, not literal event names. The important ordering is cancellation, playback stop, history reconciliation, then processing of the new turn.
6. Truncate unheard output
If the assistant generated a sentence but the user interrupted halfway through, only the delivered portion belongs in the effective conversation history. With WebRTC and SIP, the server manages the output buffer and automatic truncation. With WebSocket, your client must stop playback and send the appropriate truncation information through the session protocol, using the amount of audio actually delivered rather than the amount generated.
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This prevents a later exchange such as “What was that last thing?” from referring to an entire answer that was never audible. It also prevents the model from assuming that an instruction hidden in unheard audio was acknowledged.
7. Process the new turn against valid task state
After truncation, attach the newly completed user turn to the live session and request the next response. Re-read the application task state before invoking tools. A cancelled answer may have been describing a draft that still exists, or it may have been about a step that the user changed while interrupting. Your tool layer should validate current state instead of trusting stale prose from the cancelled response.
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8. Handle disconnects and retries
On a transport failure, mark the session as reconnecting, stop local playback, and preserve task state. When a new session is established, restore the minimum conversation context required for references and provide the structured task state needed to continue. Avoid blindly resending audio that may already have been heard; use application-level turn identifiers and idempotent tool operations.
WebRTC and WebSocket responsibilities compared
| Responsibility | WebRTC or SIP | WebSocket |
|---|---|---|
| Browser media negotiation | Negotiated media track handles the live audio path | Your application captures and sends audio frames |
| Assistant output buffer | Server-managed | Client-managed |
| Stopping on barge-in | Signal cancellation and let the server-side buffer behavior apply | Cancel the response and stop or clear local queued audio |
| Output truncation | Automatic server-side truncation is available | Client reports the portion actually played |
| Session events | Data channel | WebSocket event stream |
| Best reason to choose it | Browser voice with less custom media plumbing | Custom playback, capture, or server-side transport control |
Make follow-up questions coherent
Use conversation context for references
Keep enough live context for references to the immediately preceding exchange. “Can you say the second option again?” requires the session to know what options were just spoken and, after an interruption, which part was actually delivered.
Use task state for durable work
Conversation text is a poor database. Persist structured values such as {"step":"shipping_address","country":"..."} or the equivalent typed object in your application store, then expose only the fields and operations the assistant is authorized to use. If the user returns later, the assistant can ask a focused confirmation instead of making the user repeat every detail.
Accept typed clarification in mixed interfaces
A voice-first UI should still allow typed input. Typing a product identifier, date, or correction can supply precise context when recognition is uncertain. Feed that text into the same live session as an explicit user turn, and update task state through the same validation path used for spoken input.
Resolve ambiguous references safely
When a follow-up could refer to several items, ask a short disambiguating question rather than guessing. Preserve the unresolved choice in task state so the user can answer “the second one” without restating the entire request.
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Prompt and state rules should distinguish four cases:
- Silence: remain idle or continue listening according to the turn policy.
- Background noise or hold music: do not generate a spoken answer.
- Speech not directed to the assistant: wait rather than interrupting a nearby conversation or media playback.
- Clearly directed but unintelligible speech: ask for clarification, for example, “I didn’t catch that. Could you repeat the account number?”
The prompting guidance recommends a no-op wait behavior for audio that does not require a response. This avoids the common failure mode in which every cough, television line, or pause produces an unnecessary assistant utterance.
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Prompting for interruption recovery
Describe interruption behavior directly in the session instructions. State that the assistant should stop when the user begins a new turn, avoid claiming that unheard content was communicated, and answer follow-ups using only the corrected conversation and current task state. Also specify when to remain silent and when to ask for clarification.
Keep these instructions separate from tool authorization. The prompt can say what conversational behavior is expected; your application must still enforce permissions, validate arguments, and commit task changes transactionally.
Test the experience in realistic branches
Evaluate on the target browsers, microphones, network conditions, and speakers. The following cases expose most state bugs:
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- Interrupt after a tool call has started but before its result is spoken.
- Pause briefly mid-sentence without intending to yield the turn.
- Ask “What was that last thing?” after stopping the assistant.
- Change a form value while the assistant is reading the previous value.
- Resume a task after a reconnect or a later session.
- Play background music and verify that it does not trigger a response.
- Speak clearly addressed words that are deliberately hard to recognize and verify the clarification prompt.
- Send typed text immediately after an interrupted voice turn.
- Confirm that a cancelled response cannot execute a stale or duplicate side effect.
Review logs for three separate timestamps: speech detected, response cancelled, and audio actually played. Those measurements let you determine whether a defect is in VAD, cancellation, playback, or history reconciliation without assuming that all interruption failures have the same cause.
Common failure modes and fixes
| Symptom | Likely cause | Fix |
|---|---|---|
| The assistant keeps talking after the user starts speaking | Playback is not stopped, or a queued buffer is restarted by a late callback | Make interruption a serialized state transition and clear queued output for the selected transport |
| The assistant answers a question about words the user never heard | Generated output was retained instead of truncating to played audio | Track delivered audio and reconcile history at cancellation |
| Short pauses cut users off | VAD threshold or silence duration is too aggressive for the target speakers | Tune against representative pauses and consider semantic VAD |
| The assistant waits too long after concise commands | Boundary policy is overly conservative | Adjust timing or use a manual boundary for that interaction |
| A reconnect loses the user’s progress | Task state existed only in the live session | Persist structured application state independently of conversation audio |
| Background audio causes unwanted answers | No explicit no-op behavior for non-directed sound | Instruct the assistant to wait for silence, noise, hold music, or unrelated speech |
| A stale cancelled response changes data | Tool calls are not checked against current task state or idempotency keys | Authorize and validate each tool operation at execution time |
Security and operational safeguards
- Keep the project API key on a trusted server and issue ephemeral browser credentials.
- Require user authentication before creating a session tied to private task data.
- Scope tools to the current user and task; never rely on spoken confirmation alone for authorization.
- Redact sensitive audio and transcript content from ordinary logs, and define retention rules.
- Use idempotent tool operations so retries after reconnects cannot duplicate purchases, bookings, or updates.
- Expire abandoned sessions and release microphone resources when the user leaves the voice experience.
- Record transport, cancellation, and playback-cursor events separately so support teams can diagnose interruption bugs.
A practical decision guide
- Choose Realtime speech-to-speech with WebRTC when you are building a browser voice agent from scratch and want the platform to handle the media path and server-side output buffering.
- Choose Realtime with WebSocket when custom audio capture or playback control justifies owning cancellation and truncation mechanics.
- Choose a chained pipeline when an existing text agent or independent speech components are central to the product and your team accepts responsibility for more handoffs and turn-state coordination.
- Choose manual turn boundaries for push-to-talk or other deterministic interfaces; choose VAD when hands-free conversation is the goal.
Whichever path you select, keep the same invariant: the conversation records what the user could hear, while the application task records what the product must remember.
Conclusion
A dependable voice assistant treats barge-in as coordinated media and state management. Detect the new speech, cancel the active response, stop unplayed audio, truncate history to the audio that reached the user, and then answer the new turn using both live conversational context and durable task state. WebRTC reduces browser media plumbing; WebSocket offers control at the cost of client-owned playback and truncation. Deliberate VAD choices, explicit silence handling, typed clarification, and realistic interruption tests turn that architecture into a voice experience users can safely continue instead of repeatedly restarting.
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