chore: Update installation instructions and clone command in README.md

README.md

@@ -1,92 +1,109 @@
 # Whisper Transcribe
 
-Whisper Transcribe is a tool for transcribing video (creative captions for YouTube etc.) and correcting dialect using OpenAI's Whisper model (Speech to Text) and Chat Completions. This project extracts audio from video files, transcribes the audio, and corrects the text for dialects while maintaining the timing of the original video.
+Whisper Transcribe is an essential tool for content creators who need high-quality captions for their videos. Using OpenAI's Whisper model for Speech to Text and Chat Completions, this project extracts audio from video files, transcribes the audio, and corrects dialects while maintaining the timing of the original video. Perfect for YouTube creators, Whisper Transcribe ensures your captions are accurate and contextually appropriate, enhancing accessibility and viewer engagement.
 
 ## Features
 
 - Extracts audio from video files
-- Automatically splits the audio into smaller segments (Whisper model max filesize: 25 mb)
+- Automatically splits the audio into smaller segments (Whisper model max filesize: 25 MB)
 - Transcribes audio using OpenAI's Whisper model
-- Corrects dialects in the transcription using Chat Completions (context aware)
+- Corrects dialects in the transcription using Chat Completions (context-aware)
 
-## Installation
+## Prerequisites
 
-### Prerequisites
+### Get an OpenAI API Key
 
-#### Install FFmpeg
+1. Go to the [OpenAI API Keys page](https://platform.openai.com/api-keys).
+2. Log in or sign up for an account.
+3. Click on "Create new secret key" and copy your API key.
 
-- **Windows**: Download the latest build from the [official website](https://ffmpeg.org/download.html) and add the `bin` directory to your system's PATH.
+### Install FFmpeg
 
-- **macOS**: Install FFmpeg using [Homebrew](https://brew.sh/):
+#### Windows
 
+- **Option 1: Download from the official website**:
+  1. Download the latest build from the [official website](https://ffmpeg.org/download.html).
+  2. Extract the ZIP file to a location on your computer, e.g., `C:\ffmpeg`.
+  3. Add the `bin` directory of `ffmpeg` to your system's PATH.
+
+- **Option 2: Install using Chocolatey**:
+  1. Install Chocolatey from [chocolatey.org](https://chocolatey.org/install).
+  2. Open Command Prompt as Administrator and run:
+     ```cmd
+     choco install ffmpeg
+     ```
+
+- **Option 3: Install using winget**:
+  1. Open Command Prompt as Administrator and run:
+     ```cmd
+     winget install ffmpeg
+     ```
+
+#### macOS
+
+- Install FFmpeg using [Homebrew](https://brew.sh/):
   ```bash
   brew install ffmpeg
   ```
 
-- **Linux**: Install FFmpeg using your package manager:
+#### Linux
 
+- Install FFmpeg using your package manager:
   ```bash
   sudo apt-get install ffmpeg
   ```
 
-  ####
+## Usage (Windows Executable)
+
+1. Download the latest release from the [Releases](https://github.com/ptmrio/whisper-transcribe/releases) page.
+2. Extract the ZIP file to a directory of your choice.
+3. Open the directory and create a `.env` file with your OpenAI API key:
+   ```plaintext
+   OPENAI_API_KEY=your_openai_api_key_here
+   ```
+4. Open Command Prompt in the directory where `whisper.exe` is located.
+5. Run the executable with the required arguments:
+   ```cmd
+   whisper.exe --file="path_to_your_file.mp4" --language="DE"
+   ```
+
+6. After processing, the transcription will be saved to a file named `your_file.transcription.json` in the same directory as the original video or audio file. You can open this file with any text editor, copy the transcription, and paste it into a timing editor like YouTube Studio to auto-match the timing of your captions.
 
-- Clone the repository:
+## Installation (Universal with Python)
 
-  ```bash
-  git clone https://github.com/ptmrio/whisper-transcribe.git
-  cd project-whisper
-  ```
+### Clone the Repository
 
-### Install Whisper Transcribe (for Linux and macOS, Windows users can use the executable)
+1. Clone the repository:
+   ```bash
+   git clone https://github.com/ptmrio/whisper-transcribe.git
+   cd whisper-transcribe
+   ```
 
-1. Install the required Python packages:
+### Install Dependencies
 
+1. Install the required Python packages:
    ```bash
    pip install -r requirements.txt
    ```
 
 2. Create a `.env` file from the provided example:
-
    ```bash
    cp .env.example .env
    ```
 
 3. Add your OpenAI API key to the `.env` file:
-
    ```plaintext
    OPENAI_API_KEY=your_openai_api_key_here
    ```
 
-## Usage
-
 ### Running the Python Script
 
-```bash
-python whisper.py --file="path_to_your_file.mp4" --language="DE"
-```
-
-### Using the Executable (Windows)
-
-1. Navigate to the `dist` directory:
-
+1. Run the script with the required arguments:
    ```bash
-   cd dist
+   python whisper.py --file="path_to_your_file.mp4" --language="DE"
    ```
 
-2. Create a `.env` file from the provided example:
-
-   ```plaintext
-   OPENAI_API_KEY=your_openai_api_key_here
-   ```
-
-3. Run the executable:
-
-   ```bash
-   whisper.exe --file="path_to_your_file.mp4" --language="DE"
-   ```
-
-### Parameters
+## Parameters
 
 - `--file` (str, required): Path to the audio or video file.
 - `--model` (str, default="whisper-1"): Model to use for transcription.
@@ -95,8 +112,6 @@ python whisper.py --file="path_to_your_file.mp4" --language="DE"
 - `--response_format` (str, default="json"): Format of the transcript output.
 - `--temperature` (float, default=0): Sampling temperature between 0 and 1.
 
-#### Contributing, License, and Donations
-
 ## Contributing
 
 Contributions are welcome! Please open an issue or submit a pull request.
@@ -109,6 +124,6 @@ This project is licensed under the MIT License. See the [LICENSE](https://github
 
 If you find this project useful, consider donating to support its development:
 
-- [PayPal](paypal.me/Petermeir)
+- [PayPal](https://paypal.me/Petermeir)
 
-Thank you for your support!
+Thank you for your support!