highlight-scanner

Automatically find viral highlights in long-form videos by combining transcript, laughter, sentiment, and scene-change signals to generate a ranked list of short clips suitable for TikTok, Shorts, and Reels.

You can use AI to generate TikTok clips from podcast transcripts by analyzing sentiment, laughter, and scene changes to output structured JSON arrays of top highlights with start times, end times, and virality scores.

Laughter and sentiment detection for video highlight ranking works by combining audio and emotion signals with transcript analysis to score and rank the most engaging moments in long-form content.

The best way to extract short-form clips from gaming streams is to apply AI analysis to transcript, sentiment, and scene-change data to identify high-potential moments and return structured clip times with viral scores.

A video transcript is required to identify viral moments, as the analysis combines transcript text with laughter, sentiment, and scene-change data to accurately rank highlights for Shorts.

The AI video highlight scanner outputs a structured JSON array containing start_time, end_time, title, hook_text, reason, and supporting virality scores, ready for clipping tools to process.