Podcast Transcription: Free & AI-Powered
Turn podcast episodes into searchable, shareable text
- 99%
- Accuracy
- 99+
- Languages
- Anytime
- Cancel, no contract
- Free
- 10 min every month
Why use Podcast Transcription?
Speaker Detection
Automatically identifies host and guests. Each speaker gets a label so you know who said what.
SEO-Ready Text
Turn episodes into blog posts and show notes. Boost your podcast's discoverability in search engines.
Timestamps
Navigate long episodes with precise timestamps on every paragraph and speaker turn.
All Platforms
Upload files or paste URLs from Spotify, Apple Podcasts, RSS feeds, or direct links.
How it works
Upload or Paste URL
Upload your podcast episode file or paste a URL from any podcast platform.
AI Transcribes with Speaker Labels
Our AI identifies each speaker, generates accurate text, and adds timestamps throughout.
Use Your Transcript
Export as show notes, blog content, or subtitles. Share clips with accurate quotes.
Podcast Transcription vs typing it out by hand
Why upload-and-go beats manual transcription every time.
| Capability | CATT | Manual transcription |
|---|---|---|
| Time to first draft | Minutes per file | 8 to 10 hours per audio hour |
| Accuracy | 99% on clean audio | Depends on the typist |
| Speaker labels | Automatic | Tagged by hand |
| Languages | 99+ supported | Whatever you speak |
| Exports | TXT, DOCX, PDF, SRT, VTT | Whatever you build by hand |
| Cost | Free for the first 30 minutes | Your time, every time |
Simple pricing
Free for 10 minutes a month. Paid plans start at $9.99.
Cancel anytime. Try the free plan before you upgrade. See all plans
Frequently asked questions
Yes. Our AI detects and labels different speakers, distinguishing hosts from guests throughout the episode.
Publish the transcript as a blog post alongside your episode. Search engines index the text, driving organic traffic.
MP3, M4A, WAV, and all common podcast formats. You can also paste URLs from major podcast platforms.
Yes. Upload your video podcast file and we'll extract the audio and transcribe it with speaker labels.