Quality Estimation of English-Hindi Outputs using Naive Bayes Classifier
Gupta, Rashmi, Nisheeth Joshi, Iti Mathur · arXiv (Cornell University) · 2013
In this paper we present an approach for estimating the quality of machine translation system. There are various methods for estimating the quality of output sentences, but in this paper we focus on Naïve Bayes classifier to build model using features which are extracted from the input sentences. These features are used for finding the likelihood of each of the sentences of the training data which are then further used for determining the scores of the test data. On the basis of these scores we determine the class labels of the test data.