Hiero

Recent research presents conflicting evi- dence on whether word sense disambigua- tion (WSD) systems can help to improve the performance of statistical machine transla- tion (MT) systems. In this paper, …...

Minimum-error-rate training (MERT) is a bot- tleneck for current development in statistical machine translation because it is limited in the number of weights it can reliably opti- mize. Building on …...

We use the Margin Infused Relaxed Algo- rithm of Crammer et al. to add a large num- ber of new features to two machine transla- tion systems: the Hiero hierarchical …...

Hierarchical phrase-based translation (Hiero, (Chiang, 2005)) provides an attractive frame- work within which both short- and long- distance reorderings can be addressed consis- tently and ef�ciently. However, Hiero is gen- …...

Probabilistic phrase-based synchronous grammars are now considered promis- ing devices for statistical machine transla- tion because they can express reordering phenomena between pairs of languages. Learning these hierarchical, probabilistic devices …...

We present a novel approach for extracting a minimal synchronous context-free grammar (SCFG) for Hiero-style statistical machine translation using a non-parametric Bayesian framework. Our approach is designed to ex- tract …...

Machine translation benefits from system combination. We propose flexible interaction of hypergraphs as a novel technique combin- ing different translation models within one de- coder. We introduce features controlling the …...

Recent work has shown that word aligned data can be used to learn a model for reordering source sentences to match the target order. This model learns the cost of …...

Recent work has shown success in us- ing neural network language models (NNLMs) as features in MT systems. Here, we present a novel formulation for a neural network joint model …...