Distance phrase reordering for MOSES - User Manual and Code Guide
Yizhao Ni, Mahesan Niranjan, Craig J. Saunders, Sándor Szedmák · ePrints Soton (University of Southampton) · 2010
We describe the implementation of a novel distance phrase reordering (DPR) model for a public domain statistical machine translation (SMT) system - MOSES. The model mainly focuses on the application of machine learning (ML) techniques to a specific problem in machine translation: learning the grammatical rules and content dependent changes, which are simplified as phrase reorderings. This document serves two purposes: a user manual for the functions of the DPR model and a code guide for developers.