LibreAI / Audio / whisper-diarization
// audio · MahmoudAshraf97/whisper-diarization

whisper-diarization

Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper

★ 5.7k stars⑂ 505 forksBSD-2-Clauseupdated 2026-08
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

whisper-diarization is an open-source audio project by MahmoudAshraf97 (MahmoudAshraf97/whisper-diarization on GitHub). It has 5,661 GitHub stars and 505 forks, is released under the BSD-2-Clause license, and was last updated on GitHub on 15 August 2026.

GitHub stars
5,661
Forks
505
License
BSD-2-Clause
Last updated on GitHub
15 August 2026
Category
Audio
Listing
Full install guide
Official site
GitHub repo
// how it works

How it works

  1. Pick the job

    Transcription, synthesis, voice changing, or editing — each tool here majors in one.

  2. Install and set up

    Binaries, pip packages, or Docker; models download on first run for AI tools.

  3. Feed it audio or text

    Drop in a recording or type what you want spoken.

  4. Export the result

    WAV/MP3/OGG outputs drop straight into editors or apps.

// features

Why people love it

Speech recognition

Accurate speech-to-text for transcription workflows.

Multilingual

Dozens of languages supported, not just English.

Real-time options

Streaming transcription and TTS for live applications.

Diarization

Tell speakers apart in meetings and interviews automatically.

Voice cloning

Clone a voice from a short sample for narration and dubbing.

State-of-the-art models

Whisper-grade transcription and natural neural voices, free.

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// run it

Run it yourself

  1. Step 1 — Clone the repo

    Download the source and move into the project folder.

    git clone https://github.com/MahmoudAshraf97/whisper-diarization.git
    cd whisper-diarization
  2. Step 2 — Check the README

    Every project documents its own setup; start with install requirements.

    cat README.md | head -60
  3. Step 3 — Run it

    Follow the project's launch command — Docker, pip, npm, or a binary release.

    # see README for the exact launch command
// use cases

What you can build

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// faq

Questions, answered

Who maintains whisper-diarization?

It is an open-source project at MahmoudAshraf97/whisper-diarization with 505 forks. Check the repo's contributors and recent commits to see how active maintenance is.

Is whisper-diarization free for commercial use?

Licensed under BSD-2-Clause — check the repo for commercial-use terms.

Can I use the voices commercially?

Check each license — many allow it, but voice-cloning has ethical and legal boundaries.

How accurate is the transcription?

Whisper-class models rival paid services on clear audio; noisy recordings need cleanup first.

Which languages are supported?

Dozens; English is strongest, major world languages are solid.

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// alternatives

Alternatives in Audio

The most-starred other Audio projects in the LibreAI catalogue — the realistic shortlist if whisper-diarization is not the right fit.

Get whisper-diarization

Free and open — grab the source, star the repo, and start creating.