Turn-Taking
The mechanism by which an AI voice agent determines when a caller has finished speaking before responding.
Turn-taking is the conversational mechanism that determines whose turn it is to speak. In human conversation, turn-taking is managed through acoustic and linguistic cues — falling intonation, pauses, syntactic completion, and eye contact. AI voice agents must replicate this behavior without the non-verbal signals.
The challenge
An AI voice agent needs to respond quickly enough to feel natural (not waiting awkwardly after the caller stops) but not so quickly that it interrupts callers who are mid-thought and just pausing briefly.
Turn-taking signals used by modern AI voice agents
- Voice activity detection (VAD): Identifies when audio energy crosses a threshold, indicating speech is occurring
- End-point detection: Predicts when speech has concluded based on silence duration (simple approach) or acoustic/linguistic features (sophisticated approach)
- Prosodic cues: Rising vs. falling intonation at utterance boundaries
- Syntactic completion: Whether the last transcribed phrase is grammatically complete
- Semantic completion: Whether the caller has finished expressing their thought
Too fast vs. too slow
- Under-responding: Cutting off callers mid-thought due to overly aggressive end-point detection
- Over-waiting: Long silent pauses after callers finish speaking, making the interaction feel sluggish
TurboCall's turn-taking model combines VAD, acoustic end-pointing, and a lightweight language model that predicts utterance completion probability — balancing speed and accuracy.