redpony, smara, resnik AT umd.edu Word lattice decoding has proven useful in spoken language translation; we argue that it provides a compelling model for translation of text genres, as well. We extend lattice decoding to hierarchical phrase-based models, providing a unified treatment with phrase-based decoding by treating lattices as a case of weighted finite-state automata. In the process, we resolve a significant complication that lattice representations introduce in reordering models. Our experiments evaluating the approach demonstrate substantial gains for Chinese-English and Arabic-English translation
Nowadays, speech translation is a research problem in machine translation. The problem arises as to ...
In this paper we describe the statistical machine transla-tion system developed at ITI/UPV, which ai...
In Corpus-Based Machine Translation, the search space of the translation candidates for a given inpu...
redpony, smara, resnik AT umd.edu Word lattice decoding has proven useful in spoken language transla...
Lattice decoding in statistical machine translation (SMT) is useful in speech translation and in the...
In this paper, we start with the existing idea of taking reordering rules automatically derived from...
The idea of two-step machine translation was introduced to divide the complexity of the search space...
This thesis develops a robust inventory of large-scale lattice rescoring methods that improve the qu...
Constrained translation has improved statistical machine translation (SMT) by combining it with tran...
FBK participated in the WMT 2010 Machine Translation shared task with phrase-based Statistical Machi...
We propose a novel statistical machine translation de-coding algorithm for speech translation to imp...
FBK participated in the WMT 2010 Machine Translation shared task with phrase-based Statistical Machi...
This paper describes MISTRAL, the lattice translation system that we developed for the Italian-Engli...
Constrained translation has improved statistical machine translation (SMT) by combining it with tra...
Neural machine translation (NMT) heavily relies on word-level modelling to learn semantic representa...
Nowadays, speech translation is a research problem in machine translation. The problem arises as to ...
In this paper we describe the statistical machine transla-tion system developed at ITI/UPV, which ai...
In Corpus-Based Machine Translation, the search space of the translation candidates for a given inpu...
redpony, smara, resnik AT umd.edu Word lattice decoding has proven useful in spoken language transla...
Lattice decoding in statistical machine translation (SMT) is useful in speech translation and in the...
In this paper, we start with the existing idea of taking reordering rules automatically derived from...
The idea of two-step machine translation was introduced to divide the complexity of the search space...
This thesis develops a robust inventory of large-scale lattice rescoring methods that improve the qu...
Constrained translation has improved statistical machine translation (SMT) by combining it with tran...
FBK participated in the WMT 2010 Machine Translation shared task with phrase-based Statistical Machi...
We propose a novel statistical machine translation de-coding algorithm for speech translation to imp...
FBK participated in the WMT 2010 Machine Translation shared task with phrase-based Statistical Machi...
This paper describes MISTRAL, the lattice translation system that we developed for the Italian-Engli...
Constrained translation has improved statistical machine translation (SMT) by combining it with tra...
Neural machine translation (NMT) heavily relies on word-level modelling to learn semantic representa...
Nowadays, speech translation is a research problem in machine translation. The problem arises as to ...
In this paper we describe the statistical machine transla-tion system developed at ITI/UPV, which ai...
In Corpus-Based Machine Translation, the search space of the translation candidates for a given inpu...