ytotxt: YouTube to Text Transcription Tool

A Flask web application that automatically transcribes YouTube videos to text using OpenAI's Whisper model. The tool provides real-time progress tracking, timestamps in transcriptions, and a clean interface for managing transcripts.

Features

• 🎥 Transcribe YouTube videos using just the URL
• 🔄 Real-time progress tracking with status updates
• ⏱️ Timestamps included in transcriptions
• 💾 Automatic saving and organization of transcripts
• 📥 Easy download of transcription files
• 📚 Sidebar history of all transcribed videos
• 🎯 Clean, intuitive web interface
• 🔍 Video title and URL metadata in transcripts

Prerequisites

Before you begin, ensure you have the following installed:

• Python 3.8 or higher
• FFmpeg (required for audio processing)
• Git (for cloning the repository)

Installation

1. Install FFmpeg:

   • Ubuntu/Debian:

     sudo apt update
     sudo apt install ffmpeg

   • macOS (using Homebrew):

     brew install ffmpeg

   • Windows: Download from FFmpeg website

2. Clone the repository:

   git clone https://github.com/morriswong/ytotxt.git
   cd ytotxt

3. Create and activate a virtual environment:

   python -m venv venv
   # On Windows:
   venv\Scripts\activate
   # On macOS/Linux:
   source venv/bin/activate

4. Install Python dependencies:

   pip install -r requirements.txt

Usage

1. Start the application:

   python app.py

2. Access the web interface:

   • Open your browser and go to http://localhost:5000
   • You'll see the main transcription interface

3. Transcribe a video:

   • Paste a YouTube URL into the input field
   • Click "Transcribe"
   • Watch the real-time progress:
     1. Getting video information
     2. Downloading audio
     3. Generating transcript

4. View and Download:

   • View the transcript directly on the results page
   • Download the transcript as a text file
   • Start a new transcription or return to the main page

Project Structure

ytotxt/
├── app.py # Flask application and route handlers
├── yttotxt.py # Core transcription and YouTube download logic
├── requirements.txt # Python package dependencies
├── templates/ # HTML templates
│ ├── index.html # Main page template
│ └── result.html # Results page template
└── downloads/ # Storage for downloaded files and transcripts

How It Works

1. Video Processing:

   • Extracts video information using yt-dlp
   • Downloads only the audio stream for efficiency
   • Converts audio to required format using FFmpeg

2. Transcription:

   • Uses OpenAI's Whisper model for speech recognition
   • Processes audio in chunks for memory efficiency
   • Generates timestamps for each segment

3. File Management:

   • Creates unique directories for each video
   • Saves transcripts with metadata
   • Organizes downloads by video ID

Dependencies

• Flask: Web framework for the application
• yt-dlp: Advanced YouTube video downloader
• whisper: OpenAI's speech recognition model
• FFmpeg: Audio processing library

Development

To contribute to the project:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

Troubleshooting

Common issues and solutions:

• FFmpeg not found: Ensure FFmpeg is installed and in your system PATH
• Memory errors: Try using a smaller model in yttotxt.py (e.g., "tiny" or "base")
• Download errors: Check your internet connection and video availability

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

• OpenAI Whisper for the transcription model
• yt-dlp for YouTube video downloading
• Flask for the web framework

Support

If you encounter any issues or have questions:

1. Check the troubleshooting section
2. Open an issue on GitHub
3. Provide detailed information about your problem

---

Made with ❤️ for the open-source community