Machine translation (MT) algorithms may be classified by their operating principle. MT may be based on a set of linguistic rules, or on large bodies (corpora) of already existing parallel texts. Rule-based methodologies may consist in a direct word-by-word translation, or operate via a more abstract representation of meaning: a representation either specific to the language pair, or a language-independent interlingua. Corpora-based methodologies rely on machine learning and may follow specific examples taken from the parallel texts, or may calculate statistical probabilities to select a preferred option out of all possible translations.
