AI-Powered Intelligent Spelling Correction and Performance Evaluation System Using NLP

Abstract

The rapid expansion of digital communication has increased the demand for intelligent tools
capable of automatically detecting and correcting textual errors. Spelling inaccuracies can
significantly impact written communication quality, academic performance, and professional
documentation. Traditional spell-checking tools rely heavily on predefined dictionaries or rulebased
approaches, which often fail to understand contextual errors, morphological variations, or
user-specific writing patterns. To address these limitations, this project presents an AI-powered
Spelling Correction and Performance Evaluation System developed using Natural Language
Processing (NLP) techniques integrated into a Django-based web environment.
The proposed system allows users to input text, which is then processed by an intelligent spellchecking
algorithm. The system identifies spelling mistakes, suggests corrections, computes an
accuracy score, and stores the results for future reference. The corrected text and performance
score are saved in a database and can later be viewed in detailed reports. Personalized PDF
reports are generated using the ReportLab library, allowing users to download comprehensive
summaries of their performance, original text, corrected text, and timestamped evaluations.
A significant strength of this system is its multi-role accessibility. General users can perform spell
checks, view past test results, and track progress through a personal dashboard. Administrators
have access to an advanced analytics dashboard that provides aggregated statistics, user
performance distributions, and autogenerated bar charts based on recent results. Using Matplotlib,
visual graphs are dynamically generated and embedded into the admin dashboard, improving
interpretability and administrative decision-making