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This chapter presents in detail the main translation process of PRESEMT, delving deeper in the core of the system and its inner workings. All SMT systems (Koehn 2010), which represent the dominant approach to automatic translation, employ two statistical models in order to find the best translation in the target language: the translation model and the language model. The translation model derives from parallel corpora and can have many forms and employ various language features. Its task is to produce various TL alternative translations based on n-grams found in the SL input sentence and rank them according to their probabilities. The language model derives from the monolingual TL corpus and given a TL sentence its task is to provide a metric as to how well formed the TL is. By combining both models during the decoding process, an SMT system can provide translation alternatives using the translation …