Following is relevant to when you have a video or audio file, and you want to turn its speech into an editable text document (like a transcript):

• Options for creating editable files from video files.
• How to install Whisper on Linux
• How to install Whisper on Microsoft Windows

🔧 Options for creating editable files from a video file:

VideoPad itself cannot do speech-to-text. It’s only for editing and adding titles/captions. To convert spoken words in a file into an editable text file, you’ll need a transcription tool. Here are a few options:

1. Free, Local (no internet needed)

• Whisper (by OpenAI) → very accurate, works offline.
  • You’d install it on your computer (command line, but user-friendly once set).
  • Exports straight to a .txt file.

2. Easy Online Tools

• Otter.ai, Sonix, or Happy Scribe → upload the video/audio and get an editable transcript.
• They give you .txt or .docx downloads.

3. Quick & Free Hack

• Play your file and use Microsoft Word (latest versions) → Dictate → Transcribe (built into Word Online).
• It will automatically create an editable transcript.

🔧 How to set up Whisper locally on Linux so you can drop in any video/audio and get a text file out — completely free:

🖥 Step 1 – Install Python

Whisper runs in Python.

1. Download & install Python 3.10+.
2. When installing, tick the box “Add Python to PATH”.

⚙️ Step 2 – Install Whisper

Once Python is installed:

1. Open a terminal / command prompt.
2. Run:

pip install openai-whisper

That will fetch Whisper and its dependencies.
👉 If you get errors about ffmpeg, install it too:

• Windows: Download ffmpeg and add it to PATH.
• Mac: brew install ffmpeg
• Linux: sudo apt install ffmpeg

📂 Step 3 – Transcribe a File

Suppose your audio/video file is called myvideo.mp4 and is in your Downloads folder. Run:

whisper "C:\Users\YourName\Downloads\myvideo.mp4" --model small --output_format txt

This will:

• Use the small model (faster, decent accuracy).
• Create a text file with the transcript in the same folder.

Other useful models:

• tiny → very fast, less accurate.
• base → balance of speed/accuracy.
• medium or large → most accurate, but slow.

📄 Step 4 – Get Your Text

You’ll now see a file like:

myvideo.txt

Open it in Notepad, Word, or any editor — it’s fully editable.

📄 Step 5 – Example batch file to use Whisper to transcribe video into text files with same names as video files

whisper “D:\1.mp4” –model small –output_format txt

whisper “D:\2.mp4” –model small –output_format txt

whisper “D:\3.mp4” –model large –output_format txt

🔧 How to set up Whisper locally on Microsoft Windows so you can drop in any video/audio and get a text file out — completely free:

We’re doing local Whisper on Windows. I like it. Feels very “secret lab in the shed” energy. Let’s get you set up cleanly.

There are two main ways to install Whisper on Windows:

1. Simple + reliable (recommended): Whisper via Python
2. Faster + more efficient: whisper.cpp

I’ll walk you through both and you can pick your vibe.

🥇 Option 1 – Official OpenAI Whisper (Python version)

This is the easiest and most flexible.

Step 1: Install Python

Download Python 3.10 or 3.11 from: https://www.python.org/downloads/

During install: ✔ Check “Add Python to PATH”

After install, open Command Prompt and test:

python --version

If it prints a version number, you’re golden.

Step 2: Install FFmpeg

Whisper needs FFmpeg.

1. Download Windows build from: https://www.gyan.dev/ffmpeg/builds/
2. Extract it somewhere like:

3.  C:\ffmpeg

4. Add C:\ffmpeg\bin to your System PATH:
   • Start → Edit environment variables
   • Environment Variables
   • Edit “Path”
   • Add the bin folder

Test it:

ffmpeg -version

If it responds, good.

Step 3: Install Whisper

In Command Prompt:

pip install openai-whisper

If that fails, try:

pip install --upgrade pip

pip install openai-whisper

Step 4: Run It

To transcribe:

whisper audiofile.mp3

It will:

• Download a model automatically (first time only)
• Output a .txt file

🔬 Choosing a Model

Default is small.

Better quality:

whisper audio.mp3 --model medium

Fastest:

whisper audio.mp3 --model tiny

Highest quality:

whisper audio.mp3 --model large

🥈 Option 2 – whisper.cpp (MUCH faster on Windows)

If you want:

• Faster performance
• Lower RAM use
• CPU-optimized version

This is excellent.

Easiest way:

Download prebuilt binaries from: https://github.com/ggerganov/whisper.cpp

Or install via:

winget install whisper.cpp

Then download a model:

whisper-cli -m ggml-base.en.bin -f audio.wav

This version is dramatically faster on CPU.

💻 If You Have an NVIDIA GPU

You can install PyTorch with CUDA support and Whisper will run MUCH faster.