We have one of the largest sets of dictionaries, with thousands of rules and we use a statistical corpus to find even rare errors. A statistical grammar checker may find errors that a rule-based spellchecker does not. Usually, a rule-based spellchecker has a solid base of grammatical rules, but as you may know, there is always an exception of an exception of a rule. The collected data is too big to integrate them on a client computer, so this approach is normally not offered by most spell checkers. This approach needs a lot of precomputed data from a large text corpus (yes, Wikipedia is too small for that). The third approach is to create rules based on statistical information.For this to work, the spellchecker needs to look at several words at the same time to get the context instead of just looking for one word after another. Especially people with dyslexia know about this problem. Another example is to find homophones, words that sound more or less the same but have been used in the wrong manner. In this kind of approach, a spell checker service will detect the wrong use of the indefinite article, like using 'an” instead of “a” before a word beginning with a vowel sound.

Some spellcheckers also detect common grammatical errors through predefined rules.This is the simplest method and most spell checkers work like this. A misspelled word is identified easily as long as the dictionary is large enough to contain the word. Each word is compared to a word in a given dictionary.There are three major approaches on how to use a spell checker and check text for errors. You can even upload images with text and they will be automatically converted to editable text and checked for spelling. If you have a file you want to check for misspelled words or grammatical errors, You can upload files directly from your cloud accounts like Google Drive, Dropbox and have it error checked automatically.

Word pad spell check