Automatic text summarization from PDFs and YouTube videos using spaCy and advanced NLP techniques.

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AI-powered web app that summarizes and answers questions from PDFs, DOCX files, YouTube videos, websites using advanced NLP models.

📋 PROJECT TITLE: 🚀 Advanced Text Summarizer Using NLP with Multi-Format Support & AI Features 🎯 PROJECT OVERVIEW "An intelligent, multi-format text summarization system that extracts key information from videos, audio, PDFs, URLs, and plain text using Natural Language Processing (NLP) techniques. The system provides concise summarization

A Flask-based app that summarizes text from YouTube videos, PDFs, and plain text using NLP models, with support for translation and bilingual summaries.

TextCull - Your go-to tool for effortless content summarization. Condense YouTube videos, blogs, PDFs, and text with advanced NLP techniques. Extractive or abstractive, your choice!

Built an AI-powered desktop app to summarize study PDFs, extract key topics using KeyBERT, generate quizzes, and recommend YouTube videos for visual learning. Used PyQt5 for GUI, Hugging Face transformers for NLP, and integrated Google API for video suggestions.

AI-powered video analysis combining YOLOv8 for object detection, speech-to-text, NLP-based sentiment and summarization, word clouds, emotion charts, Flan-T5 Q&A, and PDF reports, all integrated into an interactive Streamlit dashboard.

A Python-based tool that extracts the transcript from a YouTube lecture, summarizes the content using NLP techniques, and generates a well-formatted PDF report. This project is perfect for students and educators who want quick, readable summaries of long educational videos.

A full-stack AI-powered summarization platform that allows users to generate concise summaries from plain text, PDF documents, and YouTube videos. Built using Python, Flask, React, and OpenAI APIs, this system leverages modern NLP techniques to extract key insights and improve content understanding.

The GitHub repository Information_Summarizer by Prathamesh Patil is a versatile tool built using Django, React, and Tailwind CSS. It allows users to generate summaries from various sources like plain text, PDFs, DOCX files, video transcripts, and website URLs, utilizing an advanced NLP model—Trained T5-base, trained on the abisee/cnn_dailymail 3.0.