Parallel corpora are critical resources for machine translation research and development since parallel corpora contain translation equivalences of various granularities. Manual a...
We present a method for improving word alignment for statistical syntax-based machine translation that employs a syntactically informed alignment model closer to the translation m...
In the framework of the Tc-Star project, we analyze and propose a combination of two Statistical Machine Translation systems: a phrase-based and an N-gram-based one. The exhaustiv...
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...
This paper proposes a novel maximum entropy based rule selection (MERS) model for syntax-based statistical machine translation (SMT). The MERS model combines local contextual info...