Voice activity detection distinguishes speech from silence and background noise in audio streams. VAD determines when someone is talking, enabling efficient processing and proper turn-taking in voice conversations.
How does VAD work?
VAD analyzes audio characteristics to identify speech presence. Features include energy levels, frequency patterns, and temporal dynamics. Machine learning models trained on labeled audio achieve high accuracy. VAD runs continuously during calls to track when each party is speaking.
Why does VAD matter?
VAD serves multiple purposes: triggering speech recognition only when speech is present, detecting when callers finish speaking for turn-taking, identifying interruptions for barge-in handling, and monitoring for problematic silence. Accurate VAD is foundational for natural voice interaction.
VAD in practice
A caller speaks in a noisy car environment. VAD distinguishes the caller’s voice from road noise, wind, and radio in the background. Speech recognition processes only the actual speech segments, maintaining accuracy despite the challenging acoustic conditions. Without VAD, the noise would degrade transcription quality.