Grammar Error Correction Using Natural Language Processing

In the digital era, mos t of the communication is happening through online platforms. English plays a vital role for better understanding. Good grammar helps in framing a better sentence. This demands for the development of an automatic Grammar Error Correction (GEC) tool. Many research works have been initiated to make Grammar Error Correction possible by using various machine learning algorithms. Some of the algorithms are Naive Bayes, BERT, Support Vector Machine, and ULMFIT. Among these algorithms BERT gives a comparatively best accuracy rate. The fundamental goal of this research work is to compare these algorithms with respect to accuracy Here, NLP is used for analyzing the grammatical corrections in the sentence. Further, this study can be extended to overcome the drawbacks faced by the BERT algorithm such as increase in time cons umption for training and cos t.