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I am working on a spell checker in C++ and I'm stuck at a certain step in the implementation.
Let's say we have a text file with correctly spelled words and an inputted string we would like to check for spelling mistakes. If that string is a misspelled word, I can easily find its correct form by checking all words in the text file and choosing the one that differs from it with a minimum of letters. For that type of input, I've implemented a function that calculates the Levenshtein edit distance between 2 strings. So far so good.
Now, the tough part: what if the inputted string is a combination of misspelled words? For example, "iloevcokies". Taking into account that "i", "love" and "cookies" are words that can be found in the text file, how can I use the already-implemented Levenshtein function to determine which words from the file are suitable for a correction? Also, how would I insert blanks in the correct positions?
Any idea is welcome :)
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The Levenshtein distance is usually calculated by preparing a matrix of size (M+1)x(N+1) —where M and N are the lengths of the 2 words—and looping through said matrix using 2 for loops, performing some calculations within each iteration.
The Levenshtein distance used as a metric provides a boost to accuracy of an NLP model by verifying each named entity in the entry. The vector search solution does a good job, and finds the most similar entry as defined by the vectorization.
Different definitions of an edit distance use different sets of string operations. Levenshtein distance operations are the removal, insertion, or substitution of a character in the string. Being the most common metric, the term Levenshtein distance is often used interchangeably with edit distance.
The basis of the system is the AURA modular neural network [3] described later. The spell checker uses a hybrid approach to overcome phonetic spelling errors and the four main forms of typing errors: insertion, deletion, substitu- tion, and transposition (double substitution).
Spelling correction for phrases can be done in a few ways. One way requires having an index of word bi-grams and tri-grams. These of course could be immense. Another option would be to try permutations of the word with spaces inserted, then doing a lookup on each word in the resulting phrase. Take a look at a simple implementation of a spell checker by Peter Norvig from Google. Either way, consider using an n-gram index for better performance, there are libraries available in C++ for reference.
Google and other search engines are able to do spelling correction on phrases because they have a large index of queries and associated result sets, which allows them to calculate a statistically good guess. Overall, the spelling correction problem can become very complex with methods like context-sensitive correction and phonetic correction. Given that using permutations of possible sub-terms can become expensive you can utilize certain types of heuristics, however this can get out of scope quick.
You may also consider using and existing spelling library, such as aspell.
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