Add to ORKGThis paper presents MISTRAL, an open source statistical machine translation decoder dedicated to spoken language translation. While typical machine translation systems take a written text as input, MISTRAL translates word lattices produced by automatic speech recog-nition systems. The lattices are translated in two passes using a phrase-based model. Our experiments reveal an improvement in BLEU when translating lattices instead of sentences returned by a speech recognition system. 1
<p>We propose a novel technique for adapting text-based statistical machine translation to deal with...
In this paper, we study the incorporation of statistical machine translation models to automatic spe...
We present a method for improving statistical machine translation performance by using linguisticall...
This paper describes MISTRAL, the lattice translation system that we developed for the Italian-Engli...
We propose a novel statistical machine translation de-coding algorithm for speech translation to imp...
This thesis develops a robust inventory of large-scale lattice rescoring methods that improve the qu...
Lattice decoding in statistical machine translation (SMT) is useful in speech translation and in the...
This paper describes our recent work on integrating speech recognition and machine translation for i...
Machine translation of spoken language is a challenging task that involves several natural language ...
In this paper we describe the statistical machine transla-tion system developed at ITI/UPV, which ai...
The field of machine translation is almost as old as the modern digital computer. In 1949 Warren Wea...
In this paper, we present a novel approach to integrate speech recognition and rule-based machine tr...
This paper describes the open-source Phrase-Based Statistical Machine Translation Decoder - Phrame...
A novel approach to Spoken Language Translation is proposed, which more tightly integrates Automatic...
Statistical machine translation is based on the idea to extract information from bilingual corpora, ...
<p>We propose a novel technique for adapting text-based statistical machine translation to deal with...
In this paper, we study the incorporation of statistical machine translation models to automatic spe...
We present a method for improving statistical machine translation performance by using linguisticall...
This paper describes MISTRAL, the lattice translation system that we developed for the Italian-Engli...
We propose a novel statistical machine translation de-coding algorithm for speech translation to imp...
This thesis develops a robust inventory of large-scale lattice rescoring methods that improve the qu...
Lattice decoding in statistical machine translation (SMT) is useful in speech translation and in the...
This paper describes our recent work on integrating speech recognition and machine translation for i...
Machine translation of spoken language is a challenging task that involves several natural language ...
In this paper we describe the statistical machine transla-tion system developed at ITI/UPV, which ai...
The field of machine translation is almost as old as the modern digital computer. In 1949 Warren Wea...
In this paper, we present a novel approach to integrate speech recognition and rule-based machine tr...
This paper describes the open-source Phrase-Based Statistical Machine Translation Decoder - Phrame...
A novel approach to Spoken Language Translation is proposed, which more tightly integrates Automatic...
Statistical machine translation is based on the idea to extract information from bilingual corpora, ...
<p>We propose a novel technique for adapting text-based statistical machine translation to deal with...
In this paper, we study the incorporation of statistical machine translation models to automatic spe...
We present a method for improving statistical machine translation performance by using linguisticall...