WORD REORDERING APPROACH FOR MACHINE TRANSLATION FROM ENGLISH TO DRAVIDIAN LANGUAGES

In this proposed work, word re-ordering rules for English to Dravidian languages Machine Translation System is developed. Machine Translation (MT) mainly deals with the transformation of text from one natural language to another. Generally in Machine translation, the transformation hypothesis is computationally expensive. If we perform arbitrary reordering of words while translation, the search problem will be NP-hard. If we restrict the possible reordering in an appropriate way, we obtain a polynomial-time search algorithm. Word alignment differs for a sentence from one language to another language while perform machine translation. Re-ordering the given sentence improves the performance of the statistical translation. Here word re-ordering plays a very important role. In this paper, word reordering system for English to Dravidian languages is made to solve this problem in machine translation. The dependency information’s are retrieved from Stanford parser incorporating with it; rules are created for the transformations. Transformations are then applied to English language to obtain the word order closer to the target Dravidian languages. This word reordering approach is preprocessing tool for machine translation which significantly improves the machine translation