Abstract
The English language is international language and Malayalam is a morphologically rich language. Malayalam sentence consist of root or stem word with extra suffixes. The Malayalam language uses diverse order of word as distinguish to the language English. Due to the morphological richness of Malayalam leads very few approaches for developing translation system. These approaches are divided into rule based approach and corpus based approach. Statistical machine translation model takes large set of bilingual corpus and monolingual corpus for training. The bilingual corpus contains source sentence and corresponding target sentence. The statistical approach contains translation model, language model and decoder. The translation model assign the probability of Malayalam-English sentence pair based on the maximum likelihood estimation. The decoder is the main step of statistical machine translation. It’s find the best target sentence by choosing the highest probability from the product of the translation model and language model.
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