Summarizing Text in Bangla Using Natural Language Processing

Abstract

Someone can legitimately utilise materials as a means of articulating his feelings. Accordingly, realising the material's importance is fundamental. Reading these texts and deciphering their meanings can be difficult and time-consuming. The most efficient solution to this issue is to use a machine. When it comes to artificial intelligence's potential in the realm of language learning, the content outline is a vastly underexplored but promising field of research. Research efforts should prioritise developing a system to automatically summarise content. An important part of a large report may now be written much more quickly thanks to the content summary generator. In contrast to languages like English, Bengali does not have any summarising software. The fundamental goal of this study is to extend the range of Bengali linguistic resources and developments. An attempt at a computer-generated book summary in Bengali is the subject of this inquiry. The Bengali language section of this testing was quite challenging. So far, I have set the groundwork for an automatic summarising software in the Bengali language. The information is gleaned from people's typical online behaviour. A deep learning model was used to create the summarizer. The model affects the findings of the study because it takes into consideration the fact that a faster train shortens the time it takes to recover from a tragedy. My work has improved the efficiency with which our Bengali text summarizer and its related rundown model can summarise a book in a few short sentences.