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 editing, and later as Gpt Realtime Whisper for low-latency streaming transcription.
Key facts
- Type: Speech-to-text model
- Maker: OpenAI (open-source)
- Status: Active
- Variants: OpenAI API (hosted), whisper.cpp (local — free, but RAM-intensive)
- Output: Transcript text + word-level timestamps in milliseconds
- Realtime variant: Gpt Realtime Whisper is described by OpenAI as a streaming transcription model with tunable latency down to roughly 200ms and about 80 input languages [src-083].
Use in pipeline
video-use and HyperFrames both support Whisper as a transcription backend. The word-level timestamps it produces are passed to HyperFrames to trigger animation elements at the exact spoken moment. [src-012]
Related
- See also: Openai, Video Use, Hyperframes, Elevenlabs
- Concepts: AI Video Editing Pipeline, Word Level Timestamp Sync, Live Voice Models, Voice Agents
Source references
- [src-012] Nate Herk — Video editing & content creation cluster (2026-04-15 to 2026-04-23)
- [src-083] OpenAI – "Build Hour: GPT-Realtime-2" (2026-05-13)
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From 500 indexed pages and articles.
- Wiki concept 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 Related by whisper
- 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 whisper
- 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 whisper