Hello.. Currently I have a lot of *news domain* data to train in tesseract for* non-english* language. But what I'd like to know is that in my news data, there are *many english words* and should I *remove* or *add* these english words to get the *better accuracy*. ( What I learned is that in tesseract, there are *already english trained model *and to predict the english words, we can use -l eng+(my_language)).
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