ASMR classified by trigger, intent & quality
Find your perfect
ASMR — by science
Every video classified by trigger, use-case, and quality. Not just a list — a discovery engine.
Search videos →ASMR Registry is a data-driven directory of ASMR content on YouTube. Every video is classified by its primary trigger, emotional intent, duration, and quality score — so you can find exactly what you need, not just what's popular.
Whether you need 8 hours of rain for sleep, a 15-minute tapping session for focus, or a spa roleplay for anxiety — the search engine finds it.
Learn more →How we classify videos
ASMR triggers are the specific sounds or visual patterns that produce tingling sensations. Each trigger type affects people differently — tapping works for some, whispering for others. We classify every video by its primary trigger so you can zero in on the sounds that work for you.
All 37 trigger types →Not everyone watches ASMR for the same reason. Some need it for sleep, others for focus during study sessions, and some for anxiety relief. We tag every video with its best use-case so you find content matched to your goal — not just what has the most views.
Triggers cluster into families that share acoustic or tactile properties. If you like tapping, you'll probably respond to scratching and brushing too. These groupings help you discover new triggers based on ones you already enjoy.
Nature
Voice
Touch
Desk & Objects
Materials
Mouth
Ambient
Go deeper with guides, curated lists, and gear reviews — all backed by classified data.
Every video in ASMR Registry goes through a multi-step classification pipeline. First, we extract metadata from YouTube including title, description, and channel information. Then an AI classifier identifies the primary trigger, secondary triggers, emotional intents, and intensity level on a 1–5 scale. Videos must pass a 0.7 confidence threshold before appearing in the index. Misclassified videos are flagged and corrected. The result is a structured, searchable database where every video has consistent labels — unlike algorithmic recommendations that optimize for watch time, not for what actually helps you.
Read our methodology →