Reordering Model

We propose a novel reordering model for phrase-based statistical machine transla- tion (SMT) that uses a maximum entropy (MaxEnt) model to predicate reorderings of neighbor blocks (phrase pairs). The model …...

Reordering model is important for the sta- tistical machine translation (SMT). Current phrase-based SMT technologies are good at capturing local reordering but not global reordering. This paper introduces syntactic knowledge …...

Bracketing Transduction Grammar (BTG) is a natural choice for effective integration of desired linguistic knowledge into sta- tistical machine translation (SMT). In this paper, we propose a Linguistically Anno- tated …...

We present Jane, RWTH’s hierarchical phrase-based translation system, which has been open sourced for the scientific community. This system has been in de- velopment at RWTH for the last two …...

Preordering of source side sentences has proved to be useful in improving statistical machine translation. Most work has used a parser in the source language along with rules to map …...

AbstractMT systems typically use parsers to help reorder constituents. However most languages do not have adequate treebank data to learn good parsers, and such training data is extremely time-consuming to …...

In this paper, we propose a novel re- ordering model based on sequence label- ing techniques. Our model converts the reordering problem into a sequence label- ing problem, i.e. a …...

This paper describes the phrase-based SMT systems developed for our partici- pation in the WMT13 Shared Translation Task. Translations for English↔German and English↔French were generated us- ing a phrase-based translation …...

This work is concerned with incrementally training statistical machine translation (SMT) models when new data becomes available. That, in contrast to re-training new models based on the entire accumulated data. …...

In this paper, we present a novel exten- sion of a forest-to-string machine transla- tion system with a reordering model. We predict reordering probabilities for every pair of source words …...

AbstractThe reordering model plays an important role in phrase-based statistical machine translation. However, there are few works that exploit the reordering information in neural machine translation. In this paper, we …...