Voice AI systems struggle with interruptions because they rely on simple voice activity detection (VAD) that only checks for speech presence and silence duration. Unlike humans who predict conversation endpoints using semantic content, syntax, and prosody in 200 milliseconds, current AI uses basic speech-or-no-speech detection with half-second silence thresholds. New approaches augment VAD with semantic models that analyze conversation context, while full-duplex models process input and generate output simultaneously like human minds. However, production systems still favor enhanced cascading pipelines over full-duplex models for better control and reliability.
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