Articles

For several languages only potentially non-projective dependency parses are readily available. Projectivizing the parses and utilizing them in syntax-based trans- lation systems often yields particularly bad translation results indicating that those translation models cannot properly utilize such information. We demonstrate that our system based on multi bottom-up tree transducers, which …...

This paper describes the two systems sub- mitted by LIMSI to the WMT’15 Shared Task on Automatic Post-Editing. The first one relies on a reformulation of the APE task as a Machine Translation task; the second implements a simple rule-based approach. Neither of these two systems manage to improve the …...

In this paper, we describe the “FBK English- Spanish Automatic Post-editing (APE)” systems submitted to the APE shared task at the WMT 2015. We explore the most widely used statistical APE technique (monolingual) and its most signif- icant variant (context-aware). In this exploration, we introduce some novel task-specific dense fea- …...

This paper describes the syntax-based sys- tems built at the University of Edinburgh for the WMT 2015 shared translation task. We developed systems for all language pairs except French-English. This year we focused on: translation out of En- glish using tree-to-string models; contin- uing to improve our English-German sys- tem; …...

In this year’s WMT translation task, Finnish-English was introduced as a lan- guage pair of competition for the first time. We present experiments examining sev- eral variations on a morphologically-aware statistical phrase-based machine transla- tion system for translating Finnish into English. Our system variations attempt to mitigate the issue of …...

This paper presents the machine transla- tion systems submitted by the Abu-MaTran project for the Finnish–English language pair at the WMT 2015 translation task. We tackle the lack of resources and complex morphology of the Finnish language by (i) crawling parallel and monolingual data from the Web and (ii) applying …...

This paper provides an overview of the Sheffield University submission to the WMT15 Translation Task for the Finnish- English language pair. The submitted translations were created from a system built using the CDEC decoder. Finnish is a morphologically rich language with ele- ments such as nouns and verbs carrying a …...

We present an experimental statistical tree-to-tree machine translation system based on the multi-bottom up tree trans- ducer including rule extraction, tuning and decoding. Thanks to input parse forests and a “no pruning” strategy during decod- ing, the obtained translations are compet- itive. The drawbacks are a restricted cov- erage of …...

We describe the USAAR-SAPE English– Spanish Automatic Post-Editing (APE) system submitted to the APE Task orga- nized in the Workshop on Statistical Ma- chine Translation (WMT) in 2015. Our system was able to improve upon the baseline MT system output by incorporat- ing Phrase-Based Statistical MT (PBSMT) technique into the …...

This paper describes the statistical machine translation system developed at RWTH Aachen University for the German→English translation task of the EMNLP 2015 Tenth Workshop on Statistical Machine Translation (WMT 2015). A phrase-based machine transla- tion system was applied and augmented with hierarchical phrase reordering and word class language models. Further, …...

This paper describes the UdS-Sant English–German Hybrid Machine Trans- lation (MT) system submitted to the Translation Task organized in the Work- shop on Statistical Machine Translation (WMT) 2015. Our proposed hybrid system brings improvements over the baseline system by incorporating ad- ditional knowledge such as extracted bilingual named entities and …...

This paper describes baseline systems for Finnish-English and English-Finnish ma- chine translation using standard phrase- based and factored models including mor- phological features. We experiment with compound splitting and morphological seg- mentation and study the effect of adding noisy out-of-domain data to the parallel and the monolingual training data. Our …...

This paper describes LIMSI’s submis- sions to the shared WMT’15 translation task. We report results for French-English, Russian-English in both directions, as well as for Finnish-into-English. Our submis- sions use NCODE and MOSES along with continuous space translation models in a post-processing step. The main novelties of this year’s participation …...

This paper describes the GF Wide- coverage MT system submitted to WMT 2015 for translation from English to Finnish. Our system uses a interlingua based approach, in which the interlingua is a shared formal representation, that ab- stracts syntactic structures over multiple languages. Our final submission is a re- ranked …...

Neural machine translation (NMT) systems have recently achieved re- sults comparable to the state of the art on a few translation tasks, including English→French and English→German. The main purpose of the Montreal In- stitute for Learning Algorithms (MILA) submission to WMT’15 is to evaluate this new approach on a greater …...

This paper describes the submission of the University of Edinburgh and the Johns Hopkins University for the shared transla- tion task of the EMNLP 2015 Tenth Work- shop on Statistical Machine Translation (WMT 2015). We set up phrase-based sta- tistical machine translation systems for all ten language pairs of this …...

This paper describes the AFRL-MITLL statistical MT systems and the improve- ments that were developed during the WMT15 evaluation campaign. As part of these efforts we experimented with a num- ber of extensions to the standard phrase- based model that improve performance on the Russian to English translation task cre- …...

This paper presented the joined submis- sion of KIT and LIMSI to the English to German translation task of WMT 2015. In this year submission, we integrated a neu- ral network-based translation model into a phrase-based translation model by rescor- ing the n-best lists. Since the computation complexity is one …...

The TectoMT tree-to-tree machine transla- tion system has been updated this year to support easier retraining for more transla- tion directions. We use multilingual stan- dards for morphology and syntax annota- tion and language-independent base rules. We include a simple, non-parametric way of combining TectoMT’s transfer model outputs. We submitted …...

We present the CimS submissions to the WMT 2015 Shared Task for the transla- tion direction English to German. Simi- lar to our previous submissions, all of our systems are aware of the complex nomi- nal morphology of German. In this pa- per, we combine source-side reordering and target-side compound …...