Add to ORKGIn the framework of the Tc-Star project, we analyze and propose a combination of two Statistical Machine Translation sys-tems: a phrase-based and an N-gram-based one. The exhaustive analysis includes a comparison of the translation models in terms of efficiency (number of translation units used in the search and computational time) and an examination of the errors in each system’s output. Additionally, we combine both systems, showing accuracy improvements.
Every machine translation system has some advantages. We propose an improved statistical system comb...
This work summarizes a comparison between two ap-proaches to Statistical Machine Translation (SMT), ...
This article describes in detail an n-gram approach to statistical machine translation. This ap- pro...
In the framework of the Tc-Star project, we analyze and propose a combination of two Statistical Mac...
In this paper we compare and contrast two approaches to Machine Translation (MT): the CMU-UKA Syntax...
In this paper we compare and contrast two approaches to Machine Translation (MT): the CMU-UKA Synt...
In statistical machine translation, the currently best performing systems are based in some way on p...
This article addresses the development of statistical models for phrase-based machine translation (M...
La date de publication ne nous a pas encore été communiquéeInternational audienceAs one of the most ...
Conventional confusion network based system combination for machine translation (MT) heavily relies ...
In this article, we present a novel machine translation model, the Operation Sequence Model (OSM), w...
We compare two pivot strategies for phrase-based statistical machine transla-tion (SMT), namely phra...
This paper describes the TALP phrase-based statistical machine translation system, enriched with the...
This paper describes the TALP phrase-based statistical machine translation system, enriched with the...
In this paper we describe the components of our statistical machine translation sys-tem. This system...
Every machine translation system has some advantages. We propose an improved statistical system comb...
This work summarizes a comparison between two ap-proaches to Statistical Machine Translation (SMT), ...
This article describes in detail an n-gram approach to statistical machine translation. This ap- pro...
In the framework of the Tc-Star project, we analyze and propose a combination of two Statistical Mac...
In this paper we compare and contrast two approaches to Machine Translation (MT): the CMU-UKA Syntax...
In this paper we compare and contrast two approaches to Machine Translation (MT): the CMU-UKA Synt...
In statistical machine translation, the currently best performing systems are based in some way on p...
This article addresses the development of statistical models for phrase-based machine translation (M...
La date de publication ne nous a pas encore été communiquéeInternational audienceAs one of the most ...
Conventional confusion network based system combination for machine translation (MT) heavily relies ...
In this article, we present a novel machine translation model, the Operation Sequence Model (OSM), w...
We compare two pivot strategies for phrase-based statistical machine transla-tion (SMT), namely phra...
This paper describes the TALP phrase-based statistical machine translation system, enriched with the...
This paper describes the TALP phrase-based statistical machine translation system, enriched with the...
In this paper we describe the components of our statistical machine translation sys-tem. This system...
Every machine translation system has some advantages. We propose an improved statistical system comb...
This work summarizes a comparison between two ap-proaches to Statistical Machine Translation (SMT), ...
This article describes in detail an n-gram approach to statistical machine translation. This ap- pro...