---
id: "entity-product-whisper"
type: "entity"
entityType: "tool"
canonicalName: "Whisper"
aliases: ["OpenAI Whisper"]
source_timestamps: ["00:13:25", "00:14:23"]
tags: ["audio-transcription", "openai", "asr"]
related: ["concept-programmatic-video", "claim-automated-blooper-removal"]
canonical_url: "https://github.com/openai/whisper"
---
# Whisper (OpenAI)

## Identity

An **open-source automatic speech recognition (ASR) system** by OpenAI. Provides accurate transcription with word-level timestamps.

Canonical:
- GitHub repo: https://github.com/openai/whisper
- Research announcement: https://openai.com/research/whisper

## Role in the Pipeline

[[entity-product-claude-code|Claude Code]] uses a **local installation** of Whisper to:

1. Transcribe video audio
2. Produce word-level timestamps
3. Feed those timestamps into FFmpeg-based cut scripts

This is the foundation for [[claim-automated-blooper-removal]] and the broader [[concept-programmatic-video|programmatic video editing]] story.

## Why Local Matters Here

Running Whisper locally avoids per-minute transcription fees and supports the [[claim-local-execution-efficiency|local-first efficiency argument]] — particularly important for long-form raw footage.

## See Also

- [[framework-automated-content-pipeline]] — step 3