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.

• 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.

• 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

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:

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:

3. 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. ``

• 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.

• 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.

• 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.

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