Design a realtime AI voice session around interruptions and privacy
Choose the supported connection, protect session credentials and test stopping, interrupting and recovering from a dropped call.
In brief
Realtime voice involves audio capture, transport, turn detection and response playback. A fast model cannot by itself fix microphone permission, echo or a session that continues after the user expects it to stop.
Testing interruptions makes the experience usable as a conversation rather than a queue of overlapping answers.
Build the connection boundary
For supported OpenAI browser sessions, follow the current WebRTC and session-authentication route, using your server where required. Restrict who can create sessions and their duration or usage. Do not copy a long-lived provider key into client code to simplify the demo.
Handle a real conversation
Test speaking over an answer, silence, background sound and an interrupted tool call. Make it clear when the microphone is live and when the service is responding. Do not let an interrupted spoken instruction silently trigger a consequential action without its normal authorization.
Close and recover cleanly
Stop the capture tracks and session when the user ends it, not just the audio player. Label dropped connections and reconcile pending actions before retrying. Review retention and disclosure for the chosen provider rather than implying the call is never stored under any conditions.
Before you act
Supported models, voices and connection mechanisms evolve. Microphone data goes to the configured service; do not describe a remote voice session as local processing.
What to do next
- Explain audio processing and request microphone access only for the intended session.
- Use the supported browser/server connection and protected session-credential route.
- Test interruptions, mute, stop and connection loss with harmless sample speech.
