Article and YouTube Transcript Summarizer Using Spacy and NLTK Module

Authors

  • Reshma Shaik Department of Information Technology G. H. Raisoni College of Engineering, Nagpur, Maharashtra
  • Saloni Bargat Department of Information Technology G. H. Raisoni College of Engineering,Nagpur, Maharashtra
  • Prof. Shilpa Ghode Department of Information Technology G. H. Raisoni College of Engineering,Nagpur,Maharashtra

Keywords:

Text summarization, extractive test summarization, Natural language processing

Abstract

Summarization tools have become increasingly popular among students and professionals as they can save a considerable amount of time by generating summaries quickly and efficiently. With the help of these tools, individuals can shorten lengthy texts without having to go through the tedious process of reading and summarizing the information themselves. The usefulness of summarizers is not limited to merely reducing the length of the text. They can also help individuals generate brief and concise summaries of their work that are easier to read and understand. This is especially beneficial for professionals who need to communicate complex ideas and concepts to a wider audience. Moreover, summarizers are versatile in that they can generate summaries of various lengths, depending on the needs of the individual. Some tools can provide a one-sentence summary, while others can generate a more detailed summary that covers all the important points of the text. Overall, summarization tools have proven to be a valuable asset for students and professionals alike, enabling them to streamline their work and save time while still producing high-quality summaries.

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Published

2023-06-01

How to Cite

Reshma Shaik, Saloni Bargat, & Prof. Shilpa Ghode. (2023). Article and YouTube Transcript Summarizer Using Spacy and NLTK Module . SSGM Journal of Science and Engineering, 1(1), 126–131. Retrieved from https://ssgmjournal.in/index.php/ssgm/article/view/46