We describe a novel approach for syntaxbased statistical MT, which builds on a variant of tree adjoining grammar (TAG). Inspired by work in discriminative dependency parsing, the key idea in our approach is to allow highly flexible reordering operations during parsing, in combination with a discriminative model that can condition on rich features of the sourcelanguage string. Experiments on translation from German to English show improvements over phrase-based systems, both in terms of BLEU scores and in human evaluations.Peer Reviewe
We present a method for improving statistical machine translation performance by using linguisticall...
2011-10-27Machine Translation (MT) is the task of translating a document from a source language (e.g...
Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 2010.Syntax-based statistical m...
We describe a novel approach for syntax-based statistical MT, which builds on a variant of tree adjo...
We describe a novel approach for syntax-based statistical MT, which builds on a variant of tree adjo...
Despite increasing research into the use of syntax during statistical machine translation, the incor...
We describe a method for incorporating syntactic information in statistical machine translation syst...
We describe a method for incorporating syntactic informa-tion in statistical machine translation sys...
For several languages only potentially non-projective dependency parses are readily available. Proje...
Most work in syntax-based machine trans-lation has been in translation modeling, but there are many ...
Syntax-based approaches to statistical MT require syntax-aware methods for acquiring their underlyin...
In this thesis, we take a statistical tree-to-tree approach to solving the problem of machine transl...
This paper presents a practical approach to statis-tical machine translation (SMT) based on syntacti...
In this thesis, we take a statistical tree-to-tree approach to solving the problem of machine transl...
Current methods of using lexical features in machine translation have difficulty in scaling up to re...
We present a method for improving statistical machine translation performance by using linguisticall...
2011-10-27Machine Translation (MT) is the task of translating a document from a source language (e.g...
Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 2010.Syntax-based statistical m...
We describe a novel approach for syntax-based statistical MT, which builds on a variant of tree adjo...
We describe a novel approach for syntax-based statistical MT, which builds on a variant of tree adjo...
Despite increasing research into the use of syntax during statistical machine translation, the incor...
We describe a method for incorporating syntactic information in statistical machine translation syst...
We describe a method for incorporating syntactic informa-tion in statistical machine translation sys...
For several languages only potentially non-projective dependency parses are readily available. Proje...
Most work in syntax-based machine trans-lation has been in translation modeling, but there are many ...
Syntax-based approaches to statistical MT require syntax-aware methods for acquiring their underlyin...
In this thesis, we take a statistical tree-to-tree approach to solving the problem of machine transl...
This paper presents a practical approach to statis-tical machine translation (SMT) based on syntacti...
In this thesis, we take a statistical tree-to-tree approach to solving the problem of machine transl...
Current methods of using lexical features in machine translation have difficulty in scaling up to re...
We present a method for improving statistical machine translation performance by using linguisticall...
2011-10-27Machine Translation (MT) is the task of translating a document from a source language (e.g...
Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 2010.Syntax-based statistical m...