Add to ORKGWe apply the Stat-XFER statistical transfer machine translation framework to the task of translating from French and German into En-glish. We introduce statistical methods within our framework that allow for the principled extraction of syntax-based transfer rules from parallel corpora given word alignments and constituency parses. Performance is evaluated on test sets from the 2007 WMT shared task.
International audienceDomain adaptation consists in adapting Machine Translation (MT) systems design...
The statistical framework has proved to be very successful in machine translation. The main reason f...
Statistical Machine Translation (SMT) systems are based on bilingual sentence aligned data. The qual...
We apply the Stat-XFER statistical transfer machine translation framework to the task of translating...
This paper presents the Carnegie Mellon University statistical transfer MT system submitted to the 2...
This paper describes the development of a statistical machine translation system based on the Moses ...
The goal of statistical machine translation is a transfer of unknown sentences from a source languag...
This paper describes the statistical ma-chine translation (SMT) systems devel-oped at RWTH Aachen Un...
This paper describes our statistical machine translation systems based on the Moses toolkit for the ...
RWTH participated in the shared transla-tion task of the Fourth Workshop of Sta-tistical Machine Tra...
This paper describes our Statistical Ma-chine Translation systems for the WMT10 evaluation, where LI...
This paper presents the machine trans-lation systems submitted by the Abu-MaTran project to the WMT ...
Machine translation can be considered a highly interdisciplinary and multidisciplinary field because...
The transfer-based approach to machine translation (MT) captures structural transfers between the so...
This work discusses translation results for the four Euparl data sets which were made available for ...
International audienceDomain adaptation consists in adapting Machine Translation (MT) systems design...
The statistical framework has proved to be very successful in machine translation. The main reason f...
Statistical Machine Translation (SMT) systems are based on bilingual sentence aligned data. The qual...
We apply the Stat-XFER statistical transfer machine translation framework to the task of translating...
This paper presents the Carnegie Mellon University statistical transfer MT system submitted to the 2...
This paper describes the development of a statistical machine translation system based on the Moses ...
The goal of statistical machine translation is a transfer of unknown sentences from a source languag...
This paper describes the statistical ma-chine translation (SMT) systems devel-oped at RWTH Aachen Un...
This paper describes our statistical machine translation systems based on the Moses toolkit for the ...
RWTH participated in the shared transla-tion task of the Fourth Workshop of Sta-tistical Machine Tra...
This paper describes our Statistical Ma-chine Translation systems for the WMT10 evaluation, where LI...
This paper presents the machine trans-lation systems submitted by the Abu-MaTran project to the WMT ...
Machine translation can be considered a highly interdisciplinary and multidisciplinary field because...
The transfer-based approach to machine translation (MT) captures structural transfers between the so...
This work discusses translation results for the four Euparl data sets which were made available for ...
International audienceDomain adaptation consists in adapting Machine Translation (MT) systems design...
The statistical framework has proved to be very successful in machine translation. The main reason f...
Statistical Machine Translation (SMT) systems are based on bilingual sentence aligned data. The qual...