English Auto Correct

English Auto Correct is a simple spell-correction tool based on word frequency from a large text corpus. This project uses the Leipzig English dataset to clean, prepare, and process text for auto-correct suggestions.

How It Works

The process involves:

1. Data Cleaning: Removing unwanted characters such as leading numbers and non-word characters.
2. Corpus Preparation: Building a frequency dictionary by counting word occurrences.
3. Generating Edits: Creating possible variations of the word (deletions, transpositions, replacements, insertions).
4. Search for Correct Word: Checking generated edits against the frequency dictionary.
5. Providing Suggestions: Suggesting the most likely correction based on word frequency.

Example

Here’s a simple example of how the auto-correct functionality works:

Input: "appl"
Output: "apple"

Sample Image

Here’s an illustration of how English Auto Correct works:

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