We introduce SPMT, a new class of statistical Translation Models that use Syntactified target language Phrases. The SPMT models outperform a state of the art phrase-based baseline...
Daniel Marcu, Wei Wang, Abdessamad Echihabi, Kevin...
Long distance word reordering is a major challenge in statistical machine translation research. Previous work has shown using source syntactic trees is an effective way to tackle ...
We present a quasi-synchronous dependency grammar (Smith and Eisner, 2006) for machine translation in which the leaves of the tree are phrases rather than words as in previous wor...
We propose a distance phrase reordering model (DPR) for statistical machine translation (SMT), where the aim is to learn the grammatical rules and context dependent changes using ...
We present an approach to MT between Turkic languages and present results from an implementation of a MT system from Turkmen to Turkish. Our approach relies on ambiguous lexical a...