/spell_checker

An interactive spell checker application using Python and Tkinter, featuring real-time error detection and correction suggestions powered by advanced algorithms.

Primary LanguagePythonMIT LicenseMIT

Spell Checker

📋 Overview

The Spell Checker is a Python-based application that provides an intuitive interface for real-time spell checking and correction. Developed using Tkinter, it features interactive elements that highlight misspelled words and offer correction suggestions, enhancing user experience and accessibility.

🚀 Features

  • User-Friendly Interface: Built with Tkinter, providing a clean and simple GUI.
  • Real-Time Spell Checking: Highlights errors instantly as users type.
  • Correction Suggestions: Utilizes advanced algorithms to suggest corrections.
  • Interactive Feedback: Click on highlighted words to view suggestions.

🛠️ Technologies Used

  • Python: The core programming language.
  • Tkinter: Standard GUI toolkit for Python.
  • Levenshtein Distance & Wagner-Fischer Algorithm: Employed for calculating the similarity between words and generating suggestions.

📊 Algorithms

Levenshtein Distance

A dynamic programming approach to measure the edit distance between two strings. It calculates the minimum number of single-character edits required to change one word into another.

Wagner-Fischer Algorithm

An efficient dynamic programming algorithm to compute the edit distance between two strings, widely used for applications in spell checking, DNA sequence analysis, and more. code

🎥 Demo

Watch the demo video to see the application in action.

Screen.Recording.2024-07-27.022521.mp4

📦 Installation and Usage

  1. Clone the Repository:
 git clone https://github.com/Aniruddh-482/spellChecker.git
 cd spellChecker
  1. Install Dependencies: The project primarily uses standard Python libraries. Ensure your Python environment is properly set up.
  2. Run the Application:
 python spell_checker.py

📝 How It Works

The application reads a list of correctly spelled words from a text file (words.txt). It uses the Levenshtein Distance and Wagner-Fischer algorithms to suggest the most similar correct words for any misspelled input. The user interface, built with Tkinter, provides real-time feedback and interactive suggestions.

🔧 Contributing

Contributions are welcome! Feel free to fork the repository, make improvements, and submit a pull request.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.


Made with ❤️ using Python