I have a bunch of unique full names of users. I made pseudo-physical model to emulate misprints of desktop and mobile users (hence, fatfingering, jumpy fingers, accidentals touches of touch bar etc.)
So, I have pairs like John Snow - joh Snown
I tried first Recurrent networks, LSTM, like some kind of vocabulary to "translate" from bad words to good ones, but it return only known predicted result, and when I try to put unknown last names, it returns wrong results.
I wish to find some patterns in misspelled words, and to predict correct spelling.
Can you please advice some kind of NN to cope with the task, or maybe some contributions in that domain?
P.S. Yes, I know that there exist other AI methods to get things done
P.P.S. This vocabulary is not in English, just in case
LSTM nn works nice with known names and last names endings for new last names. Right now I use 2 different nn, first to correct mistypes, second to determine first, last and middle name.
Sequence to sequence solution also can normalize name (put them in order), find sex of person, find probability of error, etc.