A Research on Grammar Correction Tool with Casual to Formal Sentence Conversion
Author(s):
Gauri Ade, Shubham Barge, Prajwal Deokar, Om Bothe, Mrs. Pallavi Shejwal
Keywords:
Natural Language Processing, Deep Learning, Sentence Conversion, Neural Networks.
Abstract
Most of the times, we as human tend to mistakes in different fields. Talking about the correction we need a tool which can help the people to correct it accordingly. GramFormer basically deals with correction of words by suggesting the next words which are grammatically correct and are constructed properly. Apart from that it also consists of a kind of conversion of sentence from Casual to formal. In daily life, we tend to write sentences which are correct but are in informal way. But in corporate word we cannot use that or some might feel bothered to write it correctly. Overall, GramFormer provides a system to the user to grammatically correct with proper sentence construction. The fundamental of this model is based on neural network and Representation Learning. The words a person chooses to use are a key indicator of their sense of style. Although everyone expresses themselves in a unique way, people adapt their speech and writing to the social setting, the audience, the interlocutor, or the level of formality of the situation. Text style transfer is the process of adapting and/or changing the stylistic approach used to write a sentence while maintaining the original sentence's meaning.
Article Details
Unique Paper ID: 157354

Publication Volume & Issue: Volume 9, Issue 6

Page(s): 779 - 782
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