We present a machine learning approach to evaluating the wellformedness of output of a machine translation system, using classifiers that learn to distinguish human reference tran...
Simon Corston-Oliver, Michael Gamon, Chris Brocket...
This paper extends the training and tuning regime for phrase-based statistical machine translation to obtain fluent translations into morphologically complex languages (we build ...
Hierarchical phrase-based machine translation can capture global reordering with synchronous context-free grammar, but has little ability to evaluate the correctness of word order...
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 ...
This paper addresses the problem of dynamic model parameter selection for loglinear model based statistical machine translation (SMT) systems. In this work, we propose a principle...