I want to do spell correction for the portuguese language, specifically for restaurant bots. The problem is that food names aren't always in portuguese as well, and for that reason are the most likely to need correction as the user would not always know how to spell it correctly.
I though of a few things. For example:
- Training the model with portugese words + food words spelled wrong, but it'd be very difficult to find these food words
- Training the model for several different languages (but I guess would make it confused and actually correct a lot of things wrong).
- Training the model with portuguese words and for the food words, use something that picks words that the user wrote and try to approximate them to the list of food words. (woudln't it be slow?)
What would be a good solution to this problem that can be fast to be used with lots of requests?