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7Evaluating the Readability of English Language Using Machine Learning Models

Shiplu Das^1*, Abhishikta Bhattacharjee², Gargi Chakraborty³ and Debarun Joardar³

¹Department of Computer Science and Engineering, Adamas University, West Bengal, India

²Department of English and Literary Studies, Brainware University, West Bengal, India

³Department of Computer Science and Engineering, Brainware University, West Bengal, India

Abstract

As a lingua franca, English is one of the world’s most extensively spoken and used languages. It is an essential tool for communication and a critical component in many sectors, including worldwide business, science, technology, and entertainment. However, its complexities and nuances can sometimes make successful interpretation difficult. To decipher the English language, a solid understanding of its syntax, vocabulary, and pronunciation is required. Understanding the complexities of its grammar structure, including syntax, conjugation, and tense, enables more precise and fluent communication of ideas and thoughts. Furthermore, having a large and diverse vocabulary and the ability to use it effectively can substantially improve one’s communication abilities. This venture aims to evaluate the meaningfulness of English language sentences utilizing a blend model methodology that joins Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). A massive dataset of sentences from different sources was gathered and pre-handled to eliminate ...