Abstract
Abstract: Interlingual is a machine translation tool that uses anartificial language to convey the meaning of reallanguages. The process of converting text from one language to another is known as machine translation.This study provides a better model of machine translation system for English-to-Kannada sentence translation that employs statistically based techniques. Here, we use Moses approach. Moses is a statistical machine translation system. systems are trained on huge amounts of parallel data as well as even bigger amounts of monolingual data in statistical machine translation. Parallel data is a set of sentences in two languages that are sentence- aligned, meaning that each sentence in one languageis matched with its translated counterpart in the other. Moses training technique takes the parallel data and infers translation correspondences betweenthe two languages of interest by looking for co- occurrences of words and segments. The two main components in Moses are the training pipeline and the decoder. The training pipeline consists of a set oftools that take raw data and convert it into a machinetranslation model. The Moses decoder determines thehighest scoring sentence in the target language that matches a given source sentence.
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