Paper Title
Identification and Text Correction Using NLP (Natural Language Processing)

Abstract
In this research paper, we look at how natural language processing can be utilized to locate and correct faults in written material (NLP). This essay investigates various strategies for locating issues with written natural language, including grammatical and semantic errors, and presents its findings. Methods based on rules, statistical methods, and techniques involving machine learning are some of the potential answers described in this article. SeveralThis research compares and contrasts several chefs to fixing faults in texts written in a natural language style methods are put to the test with a sizeable corpus of papers written in natural language as part of the research. The findings indicate that machine learning techniques are superior to human editors in terms of their ability to detect and repair faults in texts written in natural language. It is of the utmost importance to acquire the knowledge necessary to identify and rectify faults in natural language processing to raise the reliability and precision of systems that process natural language. This knowledge can be obtained from this research report.