• Bhushan Aher
• Rohit Ushir
• Prof. Shobha Raskar
• Onkar Chaudhari
• Naresh Barule

Enormous number of video recording and articles are being created and shared across the internet throughout a day. It has become really difficult to spend time watching such videos or reading such articles which may have a longer duration or length than expected and sometimes our efforts may become futile if we couldn’t find relevant information out of it. Summarizing transcripts of such videos or summarizing such articles automatically allows us to quickly lookout for the important patterns in the video and helps us save time and effort to go through the whole content of the video. The analysis is completely based on the NLP state of the art technique which is a part of artificial intelligence which helps in language recognition, summarization etc. This paper focuses on the algorithms which helps in summarizing the texts and transcripts generated. This text provides information about how we can use different algorithms to summarize the texts and also converting speech to texts for the videos which do not have transcripts and summarizing it to give an overview about the contents by extractive and abstractive text summarization techniques. This involve NLP, a type of AI that deals with analyzing, understanding and generating natural human languages so that computers can process written and spoken human languages without using computer-driven language

NLP, artificial intelligence, text summarization techniques, abstractive, extractive

"Review Of Text Summarization Techniques using NLP For Transcripts And Articles", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 12, page no.e351-e354, December-2021, Available :http://www.jetir.org/papers/JETIR2112443.pdf

"Review Of Text Summarization Techniques using NLP For Transcripts And Articles", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 12, page no. ppe351-e354, December-2021, Available at : http://www.jetir.org/papers/JETIR2112443.pdf