Automatic Ranking of Machine Translation Outputs Using Linguistic Factors

Machine Translation is the challenging problem in Indian languages. The main goal of MT research are to develop an MT systems that consistently provide high accuracy translations and that have broad coverage to handle the full range of languages. At an age of Internet and Globalization MT have a great demand. Since MT is an automated system; therefore, it is not necessary that the system will provide us the accurate translated output. To know the accuracy of the output, ranking of MT engines is required. There are many applications and statistical measures for computing the analysis of the performance of various MT engines based on various criteria; the oldest is by using human judges which can tell the quality of a translation, while newer automated methods include some linguistic factors. Human ranking is slow, time consuming and very tedious task. It takes too long to provide ranks for MT engine outputs. Due to this problem, a need for automatic ranking of MT outputs is required. For that we provide some automatic ranks for selecting the best translation among options from multiple systems which correlates better with humans.