Abstract: Text-summarization is one of the most challenging applications in the field of NLP where appropriate analysis is needed of given input text. Result of summarized text always may not identify by optimal functions, rather a better summarized result could be found by measuring sentence similarities. The current sentence similarity measuring methods only find out the similarity between words and sentences. There are two major problems to identify similarities between sentences. These problems were never addressed by previous strategies provided the ultimate meaning of the sentence and added the word order, approximately.
In this project, main objective is to try to measure sentence similarities, which will help to summarize text of any language, but we considered English here.
We have seen several text summarizing software, but the one we intend to develop will comprise of two factors summarization and translation. As English is one of the most popular languages around the globe, it is difficult for a lot of people to read long documents and lengthy texts hence summarization comes in to give a brief informative summary of the language. Not just that, we are also focusing on translation of the output into the simplest form of Hindi language.
Keywords: Text Summarizer, Translator, BERT, BART
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DOI:
10.17148/IJARCCE.2022.11367
