🎯 ElBruno.S1Mini - Clean Transcripts Automatically

Your speech-to-text results, polished in seconds

⬇️ Download Now

🤔 What Is ElBruno.S1Mini?

Have you ever used speech-to-text software and gotten a transcript full of "um," "uh," repeated words, or missing punctuation? ElBruno.S1Mini fixes all of that for you — automatically and completely offline.

This is a free, open-source tool that runs on your Windows computer. It takes your raw transcript (from Whisper, superwhisper, or any other speech recognition tool) and cleans it up so it reads like natural, professional text. No more editing hours of transcripts by hand!

✨ What Does It Do?

🗑️ Removes Fillers

Gets rid of "um," "uh," "like," "you know," and other verbal fillers that clutter your transcript.

🔄 Collapses Stutters

Turns "I-I-I think" into "I think." Repeats and stutters are automatically smoothed out.

📝 Fixes Punctuation

Adds proper commas, periods, question marks, and capitalization so your text reads naturally.

🔒 100% Local & Private

Everything runs on your computer. Your transcripts never leave your machine. No cloud, no internet required.

⚙️ How It Works

ElBruno.S1Mini uses advanced AI technology (specifically a Qwen3 model called "s1-mini") that runs through ONNX Runtime GenAI. Here's what happens behind the scenes:

  1. You provide a transcript — paste your raw speech-to-text output into the app.
  2. The AI analyzes your text — it understands the context and identifies fillers, stutters, and punctuation issues.
  3. It cleans everything up — the AI rewrites your transcript with proper grammar, punctuation, and flow.
  4. You get a polished result — copy the cleaned text or save it to a file.

The first time you run it, the app will automatically download a small AI model from HuggingFace. After that, everything works offline. The model is compact and efficient, so it runs well on most modern computers.

🚀 Download & Install

Getting started takes less than 2 minutes. Here's what to do:

Step 1: Visit this link to download the application.

📦 Get ElBruno.S1Mini

Click the link above to go to the download page.

Step 2: On that page, find the latest release and download the file.

The download page will show you the available files. Choose the one for Windows and save it to your computer.

💻 System Requirements

Operating System: Windows 10 or Windows 11 (64-bit)
RAM: 4 GB minimum (8 GB recommended)
Storage: 500 MB free space for the app and AI model
Internet: Required only for the first-time model download

📖 How to Use

1. Launch the Application

After downloading, run the application. A simple window will open.

2. Paste Your Transcript

Copy your raw transcript from any speech-to-text tool and paste it into the text box.

3. Click "Clean"

Press the button to start the cleaning process. The AI will process your text in a few seconds (longer for very long transcripts).

4. Copy or Save

Once done, your cleaned transcript appears. Copy it to your clipboard or save it as a text file.

❓ Frequently Asked Questions

Is this really free?

Yes! ElBruno.S1Mini is open-source and completely free to use. No subscriptions, no hidden costs.

Does it work with any speech-to-text tool?

Yes. As long as you have the text transcript, ElBruno.S1Mini can clean it up. It works with Whisper, superwhisper, Google Speech-to-Text, and any other tool.

How long does cleaning take?

For a typical 5-minute transcript (about 750 words), it usually takes 10-20 seconds. Longer transcripts take proportionally more time.

Will my data be sent anywhere?

No. Everything runs 100% locally on your computer. Your transcripts never leave your machine.

🛟 Need Help?

If you run into any issues or have questions, check the GitHub repository for documentation, troubleshooting guides, and community support.

🔗 Visit GitHub Repository

ElBruno.S1Mini is an open-source project. Built with ❤️ using .NET and ONNX Runtime GenAI.

Keywords: ai, asr, csharp, dotnet, dotnet10, dotnet8, huggingface, llm, local-ai, microsoft-extensions-ai, nuget, onnx, onnx-runtime, onnxruntime-genai, qwen3, s1-mini, speech-to-text, text-normalization, transcription, whisper