IBMModels

The parameters of statistical translation models are typically estimated from sentence-aligned parallel corpora. We show that significant improvements in the alignment and translation quality of such mod- els can be …...

Syntax-based statistical machine transla- tion (MT) aims at applying statistical models to structured data. In this paper, we present a syntax-based statistical ma- chine translation system based on a prob- …...

In this paper we study a set of prob- lems that are of considerable importance to Statistical Machine Translation (SMT) but which have not been addressed satis- factorily by the …...

We reveal a previously unnoticed connection between dependency parsing and statistical machine translation (SMT), by formulating the dependency parsing task as a problem of word alignment. Furthermore, we show that …...

. Although several recent studies have shown that alignment quality is a poor in- dicator of the resulting translation quality, the word alignment models currently considered to be default (the …...

Generative word alignment models, such as IBM Models, are restricted to one- to-many alignment, and cannot explicitly represent many-to-many relationships in a bilingual text. The problem is par- tially solved …...

We propose a novel extended translation model (ETM) to counteract some prob- lems in phrase-based translation: The lack of translation context when using single- word phrases and uncaptured dependen- cies …...