name: transcribe description: >- Transcribe audio files (podcasts, MP3s, interviews) using OpenAI Whisper. Use when the user wants to transcribe a podcast, audio file, or MP3. Also use when asked to "listen to" a podcast or audio. license: MIT metadata: author: spatie version: "0.0.1"

Audio Transcription

Transcribe audio files using OpenAI Whisper (installed via Homebrew).

Prerequisites

• whisper CLI must be installed: brew install openai-whisper

How to transcribe

1. Get the audio file

If given a URL, download it:

curl -L -o /tmp/audio-file.mp3 "URL_HERE"

If given a podcast name/episode, search for the RSS feed or episode page to find the MP3 URL. Podcast hosting platforms like Transistor, Buzzsprout, Libsyn typically have direct MP3 URLs in their episode pages.

2. Run Whisper

whisper /tmp/audio-file.mp3 --model small --language en --output_dir /tmp/whisper-output --output_format txt

Available models (speed vs accuracy tradeoff):

• tiny - fastest, least accurate
• base - fast, decent accuracy
• small - good balance (recommended default)
• medium - slower, better accuracy
• large - slowest, best accuracy

For non-English audio, omit the --language flag or specify the correct language code.

3. Read the output

The transcript will be at /tmp/whisper-output/audio-file.txt

Tips

• For long files (1h+), use small model to keep it reasonable
• For short files or when accuracy matters, use medium or large
• The first run downloads the model weights, subsequent runs are faster
• Output formats available: txt, vtt, srt, tsv, json
• For subtitles, use --output_format srt