Paper Contents
Abstract
In this paper we aim to create a hassle-free user experience through which a user can summarize any youtube video and save it and use it again at any given point in time. In this paper we will compare the existing youtube transcript summarizer techniques. In any instance, there is a staggering number of video recordings that are available on the internet, and also more are being created at the same time as well. That effort can be in vain if we find it hard to find time to watch longer-than-expected movies, and if useful information can't be extracted from them. Automatically summarizing movie transcripts like this can quickly identify important patterns in your videos, saving time and effort by not having to review the entire content. This work uses a flask server for text transcription. Then natural language processing (NLP) is used to summarize the transcript. About the front end, it is built using react. The website has all the necessary features which a user may require such as saving the notes for review, and a folder structure to organize similar notes. Also, we have compared the different algorithms used to summarize text on the server as well based on some metrics such as time taken, cosine values, and more.
Copyright
Copyright © 2024 Prof. Tripti Sharma. This is an open access article distributed under the Creative Commons Attribution License.
