Abstract
Statistical Machine Translation model take the view that every sentence in the target language is a translation of the source language sentence with some probability. The best translation, of course, is the sentence that has the highest probability. A large sample of human translated text (parallel corpus) is examined by the SMT algorithms for automatic learning of translation parameters. SMT has undergone tremendous development in last two decades. A large number of tools has been developed for SMT and put to work on different language pairs with fair accuracy. This paper will give brief introduction to Statistical Machine Translation; tools available for developing Statistical Machine Translation systems based on Statistical approach and their comparative study. This paper will help researcher in finding the information about SMT tools at one place.
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Kumar, A., Goyal, V. (2011). Comparative Analysis of Tools Available for Developing Statistical Approach Based Machine Translation System. In: Singh, C., Singh Lehal, G., Sengupta, J., Sharma, D.V., Goyal, V. (eds) Information Systems for Indian Languages. ICISIL 2011. Communications in Computer and Information Science, vol 139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19403-0_44
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DOI: https://doi.org/10.1007/978-3-642-19403-0_44
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