whisper-diarization

What it does

Separates the vocals, works out the distinct speakers from their voice characteristics, then attaches a speaker label to every sentence Whisper transcribes - so a multi-person meeting or interview comes out as a readable, attributed record. It runs from the command line with Python, but the project also ships a Google Colab notebook if you would rather try it in a browser first. Accuracy drops when voices are similar or people talk over each other.

Summary based on the project's own description. The Japanese page has a fuller beginner guide: setup difficulty, what to prepare, and a step-by-step start.

Screenshots & visuals

Before you start

• Setup difficultyEasy to start
• Command lineRequired
• API keyNot required
• Sends data onlineNo

Judged automatically from the project's own metadata. Always confirm on the official page.

whisper-diarization FAQ

Is whisper-diarization free?

Yes. It runs on your own machine, so there is no usage-based cost either.

Do I need to install anything or write code to use whisper-diarization?

It needs the command line. If you are not comfortable typing commands, expect to get stuck during setup.

Does whisper-diarization work on a phone?

No. It needs a computer.

Can I use whisper-diarization commercially?

The licence is BSD-2-Clause, which permits commercial use. Conditions such as keeping the copyright notice still apply, so read the licence text before shipping it inside something.

How it compares

The conditions that decide whether you can actually use it, side by side.

"Sends data out" means your input is uploaded to someone's server. Pick "No" when the material cannot leave your organisation.

Other meetings & transcription tools