Hello,

Based on the steps of Auto-correct, at the end we get the word with maximum probability, which is the word we suggest. So what exactly is the role of Minimum edit distance algorithm in this situation?

Hi @Yamini_Rao

- To evaluate the similarity between two strings. For example: ‘waht’ and ‘what’.
- To find the shortest path to go from the word ‘waht’ to the word ‘what’.

This is an additional tool for you if you need it.

For example, if you got ‘what’ as a suggestion for autocorrect from ‘waht’, you might want to know how many edits you have to take to get to the suggested word. And maybe you want to know the shortest path to get to ‘what’.

But how is it incorporated in the autocorrect model? Like any which ways we are finding all the possible words with n edits and checking if these words are there in the vocabulary right, so where does this algorithm come into picture?

It’s not. In the assignment we use it *after* we got a suggestion for correction. In reality, we might not want it to use it at all. Or we might want to use it in other areas not related to auto-correction.

As I said it is an additional tool, often useful in particular cases.

Okay, Got it!

Thankyou!