Categorization And Translation Operating System’s Assistance in Explication of Different Bangladeshi Accents

Abstract

National language of Bangladesh is Bengali and it’s also the official language used frequently. Our paper’s focal point was to categorize and differentiate West Bangla language or Bangladeshi Bangla accent in a Bengali sentence. We first amassed text from literature files. Then converted text sentence data to numeric data by using TF-IDF. After PCA application by MATLAB, final data set was being obtained. Our strategy for future will assist in developing an automatic software that detects if a sentence has been written in West Bangla or Bangladeshi Bangla and then it will do translation from one to another form. Differences between both Bangladeshi accents is already so minimum that only native speaker can identify them distinctively. There was no data available previously for this study. This work denoted that as if languages seems to be same but are unique and different in their own way and depicts the identity of two geographically separated regions. The major output of this work paid heed on identification of the form of language frequently used today. Many other studies could be conducted, based on the results of our study, on the effects of Sanskrit and Foreign literature

Keywords: Bangladeshi Bangla, Inverse Data Frequency, Linear SVM, Principal Component Analysis, Python, Term Frequency, West Bangla

Article Review Status: Published

Pages: 31-45 (Download PDF)

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