Bayesian approaches have been shown to reduce the amount of overfitting that occurs when running the EM algorithm, by placing prior probabilities on the model parameters. We appl...
As a principled approach to capturing semantic relations of words in information retrieval, statistical translation models have been shown to outperform simple document language m...
HMM-based models are developed for the alignment of words and phrases in bitext. The models are formulated so that alignment and parameter estimation can be performed efficiently....
In this paper, we argue that n-gram language models are not sufficient to address word reordering required for Machine Translation. We propose a new distortion model that can be u...
In statistical machine translation, single-word based models have an important deficiency; they do not take contextual information into account for the translation decision. A poss...