Realtime Voice and Audio Agents
Voice agents are not just chatbots with text-to-speech. They are realtime systems with audio streaming, turn detection, interruption handling, tool calls, and strict latency budgets.
The voice-agent loop
text
microphone audio
-> voice activity detection
-> speech understanding
-> model reasoning
-> optional tool calls
-> streamed speech response
-> interruption handling
Core components
| Component | Job |
|---|---|
| VAD | detect when the user starts/stops speaking |
| ASR | convert speech to text or features |
| Realtime model | reason over audio/text context |
| Tool runtime | call APIs during conversation |
| TTS | generate speech response |
| Barge-in | stop speaking when user interrupts |
Latency budget
Humans notice delay quickly. Track:
- time to detect end of turn
- model first-token latency
- tool-call latency
- speech synthesis first-audio latency
- network jitter
- interruption latency
Design tips
- Use streaming everywhere.
- Keep tool calls short and cancellable.
- Confirm before high-impact actions.
- Summarize long context instead of replaying the whole call.
- Use short spoken responses.
- Handle silence, background noise, and overlapping speech.
Voice safety
Voice agents may sound more trustworthy than they are. Add:
- explicit confirmations
- call recording disclosure where required
- safe escalation to humans
- transcript review
- rate limits
- abuse monitoring
Knowledge check
Q1: Why is interruption handling important?
Users naturally talk over voice assistants; the system must stop speaking and update context quickly.
Q2: Why should voice tools be cancellable?
Because users can change intent mid-conversation and long actions can create unsafe or stale outcomes.