Paper Title :Translation and Summarization of Arabic News Articles from Arabic to English Conducted for Text Processing

Author :Akansha Shukla, Rakesh Kumar

Article Citation :Akansha Shukla ,Rakesh Kumar , (2024 ) " Translation and Summarization of Arabic News Articles from Arabic to English Conducted for Text Processing " , International Journal of Advances in Science, Engineering and Technology(IJASEAT) , pp. 1-10, Volume-12,Issue-3

Abstract : Globalization requires accessing global news, especially Arabic news for English speakers, which faces language barriers. This study explores Arabic-English text translation and summarization, focusing on Arabic news articles. It utilizes Python libraries like Newspaper, Transformers, and Gradio to assess their effectiveness in overcoming language barriers. The research delves into challenges in Arabic text analysis and shows how Transformer-based models can handle them well. Through experiments, the study proves the method's efficacy in translating Arabic news articles accurately. It also highlights the easy integration of models into user interfaces via Gradio for interactive use. The objective of this paper is to enhance Arabic-English text processing for accessing and understanding Arabic news content. Keywords - Automatic Text Summarization, Abstractive Text Summarization, Extractive Text Summarization, Machine Learning.

Type : Research paper

Published : Volume-12,Issue-3

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