YouTube_Video_Analyzer

Overview

The YouTube Video Summarizer project is designed to help users quickly grasp the content of YouTube videos by providing a summary, key phrases, and sentiment analysis from the video transcript. This tool extracts the video transcript, generates a summary, extracts key phrases, and performs sentiment analysis to visualize the emotional tone throughout the video.

Features

• Transcript Retrieval: Fetches the transcript of a YouTube video using the YouTube Transcript API.
• Summarization: Generates a concise summary of the transcript using the BART model.
• Keyword Extraction: Identifies the most relevant keywords or phrases from the transcript.
• Sentiment Analysis: Analyzes the sentiment of the transcript and visualizes the sentiment trend over time.

Installation

1. Clone the Repository

   git clone https://github.com/kumar-017/youtube-video-summarizer.git
   cd youtube-video-summarizer

2. Create a Virtual Environment

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

3. Install Dependencies

   pip install -r requirements.txt

Usage

1. Run the Streamlit App

   streamlit run app.py

2. Enter the YouTube Video Link

   • Input the YouTube video link in the provided text box.

3. Generate Outputs

   • Click on the buttons to generate the summary, key phrases, and sentiment analysis graph.

Project Structure

• yt.py: The main file that runs the Streamlit app.
• requirements.txt: Contains the list of dependencies required for the project.
• youtube_utils.py: Contains helper functions for summarization, keyword extraction, and sentiment analysis.

Example

Here is an example of how to use the app:

1. Summarize Video

   • Enter the YouTube video link.
   • Click the "Summarize" button to get a concise summary of the video content.

2. Extract Key Phrases

   • Click the "Key Phrases" button to get a list of important phrases from the video transcript.

3. Sentiment Analysis

   • Click the "Sentiment Analysis" button to generate a sentiment trend graph for the video.

Limitations

• Transcript Availability: The tool relies on the availability of transcripts for the videos. If a transcript is not available, the tool cannot function.
• Accuracy: The quality of the summarization and keyword extraction depends on the models used and may not always be perfect.
• Processing Time: For long videos, processing can take a significant amount of time.

Future Enhancements

• Multi-language Support: Add support for transcripts in multiple languages.
• Enhanced Summarization: Improve the summarization algorithm for better accuracy.
• Customization: Allow users to customize the number of key phrases and summary length.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request or open an issue for any bugs or feature requests.

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Thank you for using the YouTube Video Analyzer! We hope this tool helps you save time and gain insights from YouTube videos more efficiently.