End-of-turn detection determines when a speaker has finished their utterance and the conversation should switch to the other party. Accurate detection enables natural turn-taking without awkward pauses or premature interruptions.
How does end-of-turn detection work?
The system analyzes multiple signals: silence duration, prosodic cues like falling intonation, syntactic completeness, and semantic context. Simple approaches use fixed silence thresholds, but sophisticated systems combine acoustic and linguistic analysis to make nuanced judgments about whether the speaker is finished.
Why does end-of-turn detection matter?
Poor detection creates conversational friction. Responding too quickly cuts off callers mid-sentence. Waiting too long creates awkward pauses that make the AI seem slow or unresponsive. Natural conversations require timing that matches human expectations for turn-taking.
End-of-turn detection in practice
A caller says “I’d like to schedule an appointment for…” then pauses to check their calendar. The system recognizes the incomplete syntax and trailing intonation, waiting rather than jumping in. When the caller continues “…next Tuesday afternoon,” the system captures the complete request before responding.