Add to ORKGThis paper describes MISTRAL, the lattice translation system that we developed for the Italian-English track of the Inter-national Workshop on Spoken Language Translation 2007. MISTRAL is a discriminative phrase-based system that translates a source word lattice in two passes. The first pass extracts a list of top ranked sentence pairs from the lattice and the second pass rescores this list with more complex fea-tures. Our experiments show that our system, when trans-lating pruned lattices, is at least as good as a fair baseline that translates the first ranked sentences returned by a speech recognition system. 1
In this paper, we give a description of the machine translation system developed at DCU that was use...
In this paper, we give a description of the Machine Translation (MT) system developed at DCU that wa...
The MIT-LL/AFRL MT system implements a standard phrase-based, statistical translation model. It inco...
This paper presents MISTRAL, an open source statistical machine translation decoder dedicated to spo...
redpony, smara, resnik AT umd.edu Word lattice decoding has proven useful in spoken language transla...
This thesis develops a robust inventory of large-scale lattice rescoring methods that improve the qu...
In this paper we describe the statistical machine transla-tion system developed at ITI/UPV, which ai...
The idea of two-step machine translation was introduced to divide the complexity of the search space...
Lattice decoding in statistical machine translation (SMT) is useful in speech translation and in the...
We propose a novel statistical machine translation de-coding algorithm for speech translation to imp...
In this paper, we give a description of the machine trans-lation system developed at DCU that was us...
In this paper, we present a novel approach to integrate speech recognition and rule-based machine tr...
This paper describes our recent work on integrating speech recognition and machine translation for i...
Nowadays, speech translation is a research problem in machine translation. The problem arises as to ...
Machine translation of spoken language is a challenging task that involves several natural language ...
In this paper, we give a description of the machine translation system developed at DCU that was use...
In this paper, we give a description of the Machine Translation (MT) system developed at DCU that wa...
The MIT-LL/AFRL MT system implements a standard phrase-based, statistical translation model. It inco...
This paper presents MISTRAL, an open source statistical machine translation decoder dedicated to spo...
redpony, smara, resnik AT umd.edu Word lattice decoding has proven useful in spoken language transla...
This thesis develops a robust inventory of large-scale lattice rescoring methods that improve the qu...
In this paper we describe the statistical machine transla-tion system developed at ITI/UPV, which ai...
The idea of two-step machine translation was introduced to divide the complexity of the search space...
Lattice decoding in statistical machine translation (SMT) is useful in speech translation and in the...
We propose a novel statistical machine translation de-coding algorithm for speech translation to imp...
In this paper, we give a description of the machine trans-lation system developed at DCU that was us...
In this paper, we present a novel approach to integrate speech recognition and rule-based machine tr...
This paper describes our recent work on integrating speech recognition and machine translation for i...
Nowadays, speech translation is a research problem in machine translation. The problem arises as to ...
Machine translation of spoken language is a challenging task that involves several natural language ...
In this paper, we give a description of the machine translation system developed at DCU that was use...
In this paper, we give a description of the Machine Translation (MT) system developed at DCU that wa...
The MIT-LL/AFRL MT system implements a standard phrase-based, statistical translation model. It inco...