The special challenge of the WMT 2007 shared task was domain adaptation. We took this opportunity to experiment with various ways of adapting a statistical ma-chine translation systems to a special do-main (here: news commentary), when most of the training data is from a dif-ferent domain (here: European Parliament speeches). This paper also gives a descrip-tion of the submission of the University of Edinburgh to the shared task. 1 Our framework: the Moses MT system The open source Moses (Koehn et al., 2007) MT system was originally developed at the Universit
A very hot issue for research and industry is how to effectively integrate machine translation (MT) ...
In this thesis we develop and evaluate a general framework for domain-adaptation of statistical mach...
Abstract tra Statistical machine translation systems are usually trained on large amounts of bilingu...
© Cambridge University Press, 2015.Statistical machine translation (SMT) is gaining interest given t...
In this paper, we tackle the problem of domain adaptation of statistical machine translation (SMT) b...
Domain adaptation for machine translation (MT) can be achieved by selecting training instances close...
This paper describes a statistical machine translation system based on freely available programs suc...
The Author(s) 2015. This article is published with open access at Springerlink.com Abstract In this ...
This paper describes a statistical machine translation system based on freely available programs suc...
Domain adaptation for machine translation (MT) can be achieved by selecting training instances close...
We tackle the problem of domain adapta-tion of Statistical Machine Translation by exploiting domain-...
Domain adaptation for machine translation (MT) can be achieved by selecting training instances close...
Globalization suddenly brings many people from different country to interact with each other, requir...
Domain adaptation for machine translation (MT) can be achieved by selecting training instances close...
Abstract. Statistical Machine Translation (SMT) systems are usually trained on large amounts of bili...
A very hot issue for research and industry is how to effectively integrate machine translation (MT) ...
In this thesis we develop and evaluate a general framework for domain-adaptation of statistical mach...
Abstract tra Statistical machine translation systems are usually trained on large amounts of bilingu...
© Cambridge University Press, 2015.Statistical machine translation (SMT) is gaining interest given t...
In this paper, we tackle the problem of domain adaptation of statistical machine translation (SMT) b...
Domain adaptation for machine translation (MT) can be achieved by selecting training instances close...
This paper describes a statistical machine translation system based on freely available programs suc...
The Author(s) 2015. This article is published with open access at Springerlink.com Abstract In this ...
This paper describes a statistical machine translation system based on freely available programs suc...
Domain adaptation for machine translation (MT) can be achieved by selecting training instances close...
We tackle the problem of domain adapta-tion of Statistical Machine Translation by exploiting domain-...
Domain adaptation for machine translation (MT) can be achieved by selecting training instances close...
Globalization suddenly brings many people from different country to interact with each other, requir...
Domain adaptation for machine translation (MT) can be achieved by selecting training instances close...
Abstract. Statistical Machine Translation (SMT) systems are usually trained on large amounts of bili...
A very hot issue for research and industry is how to effectively integrate machine translation (MT) ...
In this thesis we develop and evaluate a general framework for domain-adaptation of statistical mach...
Abstract tra Statistical machine translation systems are usually trained on large amounts of bilingu...