NLP multi-language classification task with SVM and Count Vectorizer

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Can multi-classification tasks for data-sets containing texts coming from different languages be solved with standard approached like SVM applied on senteces of both languages processed using CountVectorizer and then TfIdF measures using a data-set containing senteces coming from both languages?

In this case we would end up with a multi-lingual vocabulary where same meaning words appear in multiple languages more times, am i right?

Is it possible conceptually or is it faulty?

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