Speakr: A Self-Hosted Audio Transcription Tool for Developers

Why You Should Care About Speakr

If you’ve ever needed to transcribe meetings, interviews, or voice notes, you know the struggle: cloud-based services can be expensive, slow, or just plain unreliable with sensitive data. Enter Speakr, a self-hosted web app that lets you transcribe audio files on your own terms—no third-party APIs, no subscription fees, just you and your server.

With over 900 stars on GitHub, Speakr is clearly resonating with developers who want privacy, control, and simplicity. Whether you're archiving calls, automating note-taking, or just tired of manual transcription, this project is worth a look.

What It Does

Speakr is a lightweight Flask-based web app that:

• Accepts audio uploads (MP3, WAV, M4A, etc.)
• Transcribes them using Whisper (OpenAI’s speech recognition model)
• Stores transcripts in a searchable interface
• Supports multi-user accounts with admin controls

It’s designed to run locally or on a private server, so your data never leaves your infrastructure.

Why It’s Cool

1. Privacy-First: No reliance on external APIs—everything processes locally.
2. Easy Deployment: Docker and Docker Compose support make setup trivial.
3. Extensible: Need a different ASR (Automatic Speech Recognition) model? Swap it out—the project is modular.
4. Markdown-Friendly: Transcripts can be rendered in Markdown for easy note-taking.
5. Active Development: Recent updates (as of June 2025) show fixes for M4A processing and timezone handling.

How to Try It

1. Clone the repo:

   git clone https://github.com/murtaza-nasir/speakr.git
   

2. Set up with Docker (check the Deployment Guide):

   docker-compose -f docker-compose.example.yml up
   

3. Access the app at http://localhost:5000 and start uploading audio.

For detailed configs (like Whisper model sizes or user management), the README.md has you covered.

Final Thoughts

Speakr isn’t just another transcription tool—it’s a developer-friendly solution for folks who want control over their workflow. The AGPL-3.0 license means you can tweak it freely, and the Docker setup removes deployment headaches.

If you’re building anything that involves voice data (podcast workflows, research interviews, accessibility tools), this could save you hours. Plus, it’s a great example of how to wrap Whisper in a practical, self-hosted UI.

Try it out: murtaza-nasir/speakr

Got a use case or tweak? Star the repo or fork it—the developer’s clearly open to collaboration.