/Youmarizer

YouTube video summarizer.

Primary LanguagePythonMIT LicenseMIT

Youmarizer

Youmarizer is a Python application that extracts and summarizes content from YouTube videos. The application performs the following tasks:

  1. Downloads the video as an audio file.
  2. Processes the audio to transcribe spoken content.
  3. Summarizes the transcribed text.
  4. Extracts key points from the summary.

Features

  • Download YouTube videos and convert them to audio.
  • Split audio into manageable chunks for transcription.
  • Transcribe audio using the Vosk speech recognition model.
  • Summarize the transcribed text using a transformer-based summarization model.
  • Extract and display key points from the summary.

Requirements

  • Python 3.x
  • Required Python libraries:
    • yt-dlp
    • pydub
    • tqdm
    • vosk
    • transformers
    • colorama

You can install the necessary libraries using pip:

pip install yt-dlp pydub tqdm vosk transformers colorama

Installation

  1. Clone the repository:

    git clone https://github.com/yourusername/youmarizer.git

  2. Install ffmpeg: Ensure that ffmpeg is installed on your system. You can download it from FFmpeg’s official website and follow the installation instructions for your operating system.

  3. Download the Vosk model: Download the Vosk model from here and extract it to a directory named vosk-model-small-en-us-0.15 within your project folder.

  4. Install Python dependencies: Make sure you have all the required libraries installed by running:

Usage

  1. Run the application: Execute the main.py script

    python main.py

  2. Enter the YouTube video URL when prompted:

Enter the YouTube video URL:

  1. View the results: - The summary will be displayed, and you will be prompted to press Enter to continue. - Key points extracted from the summary will be displayed with bullet points. ``

Project Structure

  • main.py: The main script to run the application.
  • audio_processor.py: Contains functions for downloading, splitting, and processing audio.
  • transcriber.py: Contains functions for speech recognition and transcription.
  • summarizer.py: Contains functions for text summarization and key point extraction.

Notes

  • Ensure you have ffmpeg installed for audio processing. You can download it from FFmpeg’s official website.
  • Adjust the chunk_length_ms parameter in process_audio if you encounter performance issues or need finer control over chunk sizes.

Troubleshooting

  • Error: ffmpeg not found: Make sure ffmpeg is installed and added to your system’s PATH.
  • Model not found: Verify that the Vosk model is correctly downloaded and extracted in the specified directory.

License

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