Recent papers have described machine translation (MT) based on an automatic post-editing or serial combination strategy whereby the input language is first translated into the target language by a rule-based MT (RBMT) system, then the target language output is automatically post-edited by a phrase-based statistical machine translation (SMT) system. This approach has been shown to improve MT quality over RBMT or SMT alone. In this previous work, there was a very loose coupling between the two systems: the SMT system only had access to the final 1-best translations from RBMT. Furthermore, the previous work involved European language pairs and relatively small training corpora. In this paper, we describe a more tightly integrated serial combin...
Since statistical machine translation (SMT) and translation memory (TM) complement each other in mat...
This paper proposes the use of rules automatically extracted from word aligned training data to mod...
The paper explores a way to learn post-editing fixes of raw MT outputs automatically by combining tw...
This article describes a machine translation system based on an automatic post-editing strategy: ini...
We propose to use a statistical phrase-based machine translation system in a post-editing task: the ...
We have developed a two-stage machine translation (MT) system. The first stage is a rule-based machi...
Statistical machine translation systems are usually trained on large amounts of bilingual text and o...
Two of the most popular Machine Translation (MT) paradigms are rule based (RBMT) and corpus based, w...
In this article we address the issue of generating diversified translation systems from a single Sta...
Since sentences in patent texts are long, they are difficult to translate by a machine. Although sta...
This paper proposes to use monolingual collocations to improve Statistical Ma-chine Translation (SMT...
It is generally acknowledged that the performance of rule-based machine translation (RMBT) systems c...
We describe a hybridisation strategy whose objective is to integrate linguistic resources from shall...
Statistical machine translation systems are usually trained on large amounts of bilingual text (used...
This article addresses the development of statistical models for phrase-based machine translation (M...
Since statistical machine translation (SMT) and translation memory (TM) complement each other in mat...
This paper proposes the use of rules automatically extracted from word aligned training data to mod...
The paper explores a way to learn post-editing fixes of raw MT outputs automatically by combining tw...
This article describes a machine translation system based on an automatic post-editing strategy: ini...
We propose to use a statistical phrase-based machine translation system in a post-editing task: the ...
We have developed a two-stage machine translation (MT) system. The first stage is a rule-based machi...
Statistical machine translation systems are usually trained on large amounts of bilingual text and o...
Two of the most popular Machine Translation (MT) paradigms are rule based (RBMT) and corpus based, w...
In this article we address the issue of generating diversified translation systems from a single Sta...
Since sentences in patent texts are long, they are difficult to translate by a machine. Although sta...
This paper proposes to use monolingual collocations to improve Statistical Ma-chine Translation (SMT...
It is generally acknowledged that the performance of rule-based machine translation (RMBT) systems c...
We describe a hybridisation strategy whose objective is to integrate linguistic resources from shall...
Statistical machine translation systems are usually trained on large amounts of bilingual text (used...
This article addresses the development of statistical models for phrase-based machine translation (M...
Since statistical machine translation (SMT) and translation memory (TM) complement each other in mat...
This paper proposes the use of rules automatically extracted from word aligned training data to mod...
The paper explores a way to learn post-editing fixes of raw MT outputs automatically by combining tw...