Add to ORKGWe report on findings of exploiting large data sets for translation modeling, language mod-eling and tuning for the development of com-petitive machine translation systems for eight language pairs.
Statistical machine translation systems are usually trained on large amounts of bilingual text (used...
Statistical machine translation systems are usually trained on large amounts of bilingual text and o...
Statistical machine translation (SMT) systems use statistical learning methods to learn how to trans...
Sentence-aligned bilingual texts are a crucial resource to build statistical machine translation (SM...
Machine translation is the application of machines to translate text or speech from one natural lang...
Parallel corpus is an indispensable resource for translation model training in statistical machine t...
We report on efforts to build large-scale translation systems for eight European language pairs. We ...
The performance of Phrase-Based Statistical Machine Translation (PBSMT) systems mostly depends on ...
Statistical Machine Translation (SMT) models learn how to translate by examining a bilingual paralle...
Abstract. Statistical Machine Translation (SMT) systems are usually trained on large amounts of bili...
We present an extensive experimental study of Phrase-based Statistical Machine Translation, from the...
We present an extensive experimental study of Phrase-based Statistical Machine Translation, from the...
This paper presents our on-going efforts to develop a comprehensive data set and benchmark for machi...
Statistical machine translation relies heavily on available parallel corpora, but SMT may not have t...
Domain adaptation has recently gained interest in statistical machine translation to cope with the p...
Statistical machine translation systems are usually trained on large amounts of bilingual text (used...
Statistical machine translation systems are usually trained on large amounts of bilingual text and o...
Statistical machine translation (SMT) systems use statistical learning methods to learn how to trans...
Sentence-aligned bilingual texts are a crucial resource to build statistical machine translation (SM...
Machine translation is the application of machines to translate text or speech from one natural lang...
Parallel corpus is an indispensable resource for translation model training in statistical machine t...
We report on efforts to build large-scale translation systems for eight European language pairs. We ...
The performance of Phrase-Based Statistical Machine Translation (PBSMT) systems mostly depends on ...
Statistical Machine Translation (SMT) models learn how to translate by examining a bilingual paralle...
Abstract. Statistical Machine Translation (SMT) systems are usually trained on large amounts of bili...
We present an extensive experimental study of Phrase-based Statistical Machine Translation, from the...
We present an extensive experimental study of Phrase-based Statistical Machine Translation, from the...
This paper presents our on-going efforts to develop a comprehensive data set and benchmark for machi...
Statistical machine translation relies heavily on available parallel corpora, but SMT may not have t...
Domain adaptation has recently gained interest in statistical machine translation to cope with the p...
Statistical machine translation systems are usually trained on large amounts of bilingual text (used...
Statistical machine translation systems are usually trained on large amounts of bilingual text and o...
Statistical machine translation (SMT) systems use statistical learning methods to learn how to trans...