whisper-transcribe

name	whisper-transcribe
description	Transcribes audio and video files to text using OpenAI's Whisper CLI with contextual grounding. Converts audio/video to text, transcribes recordings, and creates transcripts from media files. Use when asked to "whisper transcribe", "transcribe audio", "convert recording to text", or "speech to text". Uses markdown files in the same directory as context to improve transcription accuracy for technical terms, proper nouns, and domain-specific vocabulary.
version	1.0.0
category	media-processing
triggers	["whisper","transcribe","transcription","audio to text","video to text","speech to text","convert recording","meeting transcript",".mp3",".wav",".m4a",".mp4",".webm"]
author	Claude Code
license	MIT
tags	["whisper","transcription","audio","video","speech-to-text","context-grounding"]

Whisper Transcribe Skill

Transcribe audio and video files to text using OpenAI's Whisper with contextual grounding from markdown files.

Purpose

Intelligent audio/video transcription that:

1. Converts media files to accurate text transcripts
2. Uses markdown context files to correct technical terms, names, and jargon
3. Handles various audio/video formats (mp3, wav, m4a, mp4, webm, etc.)

When to Use

• User asks to transcribe an audio or video file
• User wants to convert a recording to text
• User mentions "whisper" in context of transcription
• User needs meeting notes or interview transcripts
• User has media files with domain-specific terminology

Installation

macOS (Recommended for MacBook Pro)

# Install via Homebrew (recommended)
brew install ffmpeg openai-whisper

# Verify installation
whisper --version

Linux/pip Installation

# Install ffmpeg first
sudo apt install ffmpeg  # Debian/Ubuntu
# or: sudo dnf install ffmpeg  # Fedora

# Install Whisper
pip install openai-whisper

Verify Installation

whisper --version
ffmpeg -version

Transcription Workflow

Step 1: Identify Media File and Context

1. Locate the audio/video file to transcribe
2. Check for markdown files in the same directory (context files)
3. If no context files exist, optionally create one using assets/context-template.md

Step 2: Run Whisper Transcription

Basic transcription:

whisper "/path/to/audio.mp3" --output_dir "/path/to/output"

With model selection (trade-off: speed vs accuracy):

# Fast (less accurate)
whisper "audio.mp3" --model tiny

# Balanced (recommended)
whisper "audio.mp3" --model base

# High quality
whisper "audio.mp3" --model small


whisper  --model medium
whisper  --model large