The Edinburgh/LMU Hierarchical Machine Translation System for WMT 2016
نویسندگان
چکیده
This paper describes the hierarchical phrase-based machine translation system built jointly by the University of Edinburgh and the University of Munich (LMU) for the shared translation task at the ACL 2016 First Conference on Machine Translation (WMT16). The WMT16 Edinburgh/LMU system was trained for translation of news domain texts from English into Romanian. We participated in the shared task for machine translation of news under “constrained” conditions, i.e. using the provided training data only.
منابع مشابه
The QT21/HimL Combined Machine Translation System
This paper describes the joint submission of the QT21 and HimL projects for the English→Romanian translation task of the ACL 2016 First Conference on Machine Translation (WMT 2016). The submission is a system combination which combines twelve different statistical machine translation systems provided by the different groups (RWTH Aachen University, LMU Munich, Charles University in Prague, Univ...
متن کاملLMU Munich's Neural Machine Translation Systems for News Articles and Health Information Texts
This paper describes the LMU Munich English→German machine translation systems. We participated with neural translation engines in the WMT17 shared task on machine translation of news, as well as in the biomedical translation task. LMU Munich’s systems deliver competitive machine translation quality on both news articles and health information texts.
متن کاملEdinburgh Neural Machine Translation Systems for WMT 16
We participated in the WMT 2016 shared news translation task by building neural translation systems for four language pairs, each trained in both directions: English↔Czech, English↔German, English↔Romanian and English↔Russian. Our systems are based on an attentional encoder-decoder, using BPE subword segmentation for open-vocabulary translation with a fixed vocabulary. We experimented with usin...
متن کاملThe RWTH Aachen University English-Romanian Machine Translation System for WMT 2016
This paper describes the statistical machine translation system developed at RWTH Aachen University for the English→Romanian translation task of the ACL 2016 First Conference on Machine Translation (WMT 2016). We combined three different state-ofthe-art systems in a system combination: A phrase-based system, a hierarchical phrase-based system and an attentionbased neural machine translation sys...
متن کاملThe JHU Machine Translation Systems for WMT 2016
This paper describes the submission of Johns Hopkins University for the shared translation task of ACL 2016 First Conference on Machine Translation (WMT 2016). We set up phrase-based, hierarchical phrase-based and syntax-based systems for all 12 language pairs of this year’s evaluation campaign. Novel research directions we investigated include: neural probabilistic language models, bilingual n...
متن کامل