Rule Based Approach to Extract Metadata In Scientific PDF Document

Authors: Vijaya Sunil Ruperi, Bhagyashree Ashok Jadhav, Trupti Chandrakant Jadhav, Bheembai Kareppa Kavaldar, Prof. Naresh Shende

Country: India

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Abstract: With the availability of World Wide Web in every corner of the world these days, the amount of information on the internet is growing at an exponential rate. However, given the hectic schedule of people and the immense amount of information available, there is increase in need for information abstraction or summarization. Be it browsing through the seemingly endless pages of terms and conditions on an important official document or kicking back and flipping through an intriguing eBook- reading is quite an undeniable and inescapable part of our everyday lives. However, reading anything demands our complete undivided attention making it nearly impossible for us to multitask. This Online PDF to Audio Converter and Translator was created by using Python (Django) can instantly convert any PDF text into audio. Along with reading any PDF document out loud, this application can also translate and vocalize any text into up to five languages. Text summarization presents the user a shorter version of text with only vital information and thus helps him to understand the text in shorter amount of time. The goal of this project is to condense the documents or reports into a shorter version and preserve important contents convert that summarized text into audio for better understanding of the user. Also projects convert the generated summery to the audio for better understanding.

Keywords: Python, NPL, PDF Extraction, audio converter, machine learning

Paper Id: 230593

Published On: 2024-04-21

Published In: Volume 12, Issue 2, March-April 2024

Cite This: Rule Based Approach to Extract Metadata In Scientific PDF Document - Vijaya Sunil Ruperi, Bhagyashree Ashok Jadhav, Trupti Chandrakant Jadhav, Bheembai Kareppa Kavaldar, Prof. Naresh Shende - IJIRMPS Volume 12, Issue 2, March-April 2024.

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