video-use
Open-source Python library for AI-powered video editing. Handles the transcript generation and editing phase (filler word removal, silence cutting, retake detection) using word-level timestamps, then passes structured output downstream to HyperFrames or Remotion for motion graphics.
Key facts
- Type: Video editing library (Python)
- Status: Active (open-source)
- Transcription backends: OpenAI Whisper, Whisper.cpp (local, free, RAM-intensive), ElevenLabs API
- Output: Edited video (cuts applied) + word-level timestamp JSON for motion graphic sync
- Integration: Works with both Remotion and HyperFrames for the animation step
What it does in the pipeline
In the AI video editing pipeline: raw recording → video-use (transcribe + cut filler/silences/retakes) → HyperFrames/Remotion (add motion graphics, sync animations to word timestamps) → FFmpeg → MP4 [src-012]
Related
- See also: Hyperframes, Remotion, Whisper, Elevenlabs
- Concepts: AI Video Editing Pipeline, Word Level Timestamp Sync
Source references
- [src-012] Nate Herk — Video editing & content creation cluster (2026-04-15 to 2026-04-23)
Keep reading from this thread
From 500 indexed pages and articles.
- Wiki concept AI Video Editing Pipeline End-to-end agentic pipeline for producing edited, motion-graphic-enhanced video from a raw recording using Claude Code as orchestrator. Related by word
- Wiki concept Word-Level Timestamp Sync Technique in AI video editing where transcription (Whisper or ElevenLabs) produces millisecond-precision timestamps per spoken word, used to trigger motion graphic animations at Related by word
- Wiki concept OpenAI Whisper Speech-to-text model family used for video transcription and realtime speech recognition. In the wiki it first appears as the transcription backend for AI video Related by word