PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Distance phrase reordering for moses - user manual and code guide
Yizhao Ni, Mahesan Niranjan, Craig Saunders and Sandor Szedmak
(2010) Technical Report. University of Southampton, Southampton, UK.

Abstract

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.

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EPrint Type:Monograph (Technical Report)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:7258
Deposited By:Ni Yizhao
Deposited On:14 March 2011