YouTube Video Summarizer Using ASR

Platforms like YouTube have revolutionized the way people distribute and consume information in the video-dominated digital age. However, viewers who are trying to get pertinent information quickly may find it difficult due to the sheer volume of videos. This research describes a system for summarizing YouTube videos that effectively extracts information using Term Frequency-Inverse Document Frequency (TF-IDF) and Automatic Speech Recognition (ASR) analysis. ASR translates audio to text, and TF-IDF finds the most important information for brief summaries. Empirical validation supports the optimization of usability through automation and personalization. The technology facilitates navigation through large amounts of video footage by supporting Natural Language processing (NLP) and information retrieval.