I would like to add YouTube video summarizer

[rahulbamnuya]

Here’s how you can structure the details of your YouTube video summarizer Python project:

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🔍 Problem Description:
The problem addressed by this project is the increasing consumption of video content on platforms like YouTube, where users often need a quick summary to decide whether a video is worth watching. Manually watching and summarizing long videos can be time-consuming. This project aims to automatically summarize the key points of a YouTube video by analyzing its transcript, providing a concise version that saves the user's time.

🧠 Model Description:
The project will use Natural Language Processing (NLP) techniques to summarize the video transcripts. The model may be built using TextRank or Abstractive Summarization methods such as transformer-based models (like BERT or GPT) to generate summaries. These techniques allow the model to extract the most important information from the transcript, condense it, and present it in a coherent and brief format. We will use YouTube’s transcript data (available via YouTube’s API) and tools like spaCy, NLTK, or Hugging Face Transformers to implement the summarizer.

⏲️ Estimated Time for Completion:

• Research and dataset collection (YouTube API integration): 1-2 days.
• Model selection and implementation (TextRank or transformer model): 2-3 days.
• Summarization logic implementation and testing: 2 days.
• Final integration and documentation: 1 day.
• Total estimated time: 6-8 days.

🎯 Expected Outcome:
The expected outcome is a fully functioning Python tool that can take a YouTube video link as input, retrieve the transcript (or auto-generate it using API services if not available), and return a concise summary of the video content. The tool will be able to:

1. Extract the transcript from the YouTube video.
2. Apply the summarization algorithm to condense the transcript into key points.
3. Output the summary to the user in text format, optionally displaying it in the terminal or saving it as a file.

📄 Additional Context:

• The project may involve handling noisy transcripts with errors, so additional preprocessing steps (such as cleaning, removing irrelevant parts like ads) will be added.
• Video transcript availability will depend on YouTube’s API limits, so edge cases where a transcript is unavailable will be handled.

To be Mentioned while taking the issue:

• Participant Role: Open Source Program (e.g., Hacktoberfest ,gssoc-extd) contributor.

[yashasvini121]

Sure @rahulbamnuya. Please fork the NLP branch and submit your PR to that branch only.