Audio event detection
Also known as: sound event detection, audio tagging, acoustic event detection
AI that recognizes meaningful sounds in a recording, such as cheering, impacts, splashes, engine revs or laughter, to help find important moments.
Updated
What it means
Sound often marks the best moments before the picture does. Friends shouting, a crowd cheering, a board slapping the water, a crash, an engine screaming or a burst of laughter all signal that something happened. Audio event detection models learn to recognize these sounds and mark when they occur.
Combined with action recognition and visual signals, audio helps AI editing tools judge which moments are exciting. A jump with cheering afterwards probably matters more than one in silence.
Audio analysis is part of multimodal video analysis, where several kinds of information are considered together.
How it works in practice
Keep camera microphones uncovered where possible, and avoid taping over them, since even rough audio helps analysis. Cases and housings muffle sound, which reduces useful audio signals. A clipped-on external microphone with its own foam keeps impacts and shouts recognizable at speed.
Wind is the biggest enemy of camera audio. Wind noise can drown out voices and impacts. Wind-reduction settings and foam or furry covers help in many situations, even on small cameras.
Recording natural sound also benefits your edit directly, since ambient sound and reactions bring footage to life between music sections. A short burst of a friend yelling after a landing often says more than any title card.
What to watch out for
Loud constant noise, such as wind at speed, engines or rushing water, can mask the sounds that matter. Detectors may miss moments or flag noise as events.
Background music playing during recording, for example at a bike park or event, can confuse analysis and may trigger Content ID claims if it stays in the final video.
Silence is not boring by default. Some of the best moments, like a calm sunset view or a drone shot without sound, carry no audio events at all, so good tools never rely on sound alone.
How RawClip handles it
RawClip uses AI analysis of your footage to find motion, jumps, faces and peak action, then cuts the best moments to the beat of the music. Upload clips with their original sound, and the AI builds your highlight.