• laxman singh
• Ram kumar sharma
• Nikhil saini
• Mrytunjay singh

Abstract— This project focuses on data collection and writing, aiming to develop a framework for efficiently summarizing extensive knowledge available on the Internet. The proposed framework leverages morphological content and semantic information to sift through the vast amount of data online. The current information landscape is overwhelming, making it challenging for individuals to extract pertinent details quickly. The sheer volume of data on the Internet poses difficulties in searching for and assimilating relevant information from diverse sources. The solution lies in the development of an automatic writing system to address these challenges effectively. Summary summarization, a crucial aspect of this framework, involves identifying and condensing the most important and useful information from a given dataset. The goal is to create a concise version while retaining the full purpose of the original data entry. The significance of this approach becomes apparent in the face of the daunting task of making sense of big data, streamlining the process and facilitating efficient extraction of meaningful insights

Keywords— Natural Language Processing (NLP), SBERT, Transformer, Hugging face, Tokens, Machine Learning, Summarization

"Data summerization and voice assistant", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.g532-g535, March-2024, Available :http://www.jetir.org/papers/JETIR2403673.pdf

"Data summerization and voice assistant", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppg532-g535, March-2024, Available at : http://www.jetir.org/papers/JETIR2403673.pdf