Articles

We participated in the WMT 2016 shared news translation task on English ↔ Chi- nese language pair. Our systems are based on the encoder-decoder neural machine translation model with the attention mech- anism. We employ the Gated Recurrent Unit (GRU) with the linear associative connection to build deep encoder and …...

This paper describes the monomodal and multimodal Neural Machine Translation systems developed by LIUM and CVC for WMT17 Shared Task on Multimodal Translation. We mainly explored two mul- timodal architectures where either global visual features or convolutional feature maps are integrated in order to benefit from visual context. Our final …...

This paper documents an undergraduate course at Hunter College, in which one instructor, six undergraduates, and one high school student built 17 machine translation systems in six months from scratch. The team successfully partici- pated in the second Conference on Ma- chine Translation (WMT17) evaluation on the news task in …...

In this paper, we attempt to improve Statistical Machine Translation (SMT) systems between Czech, Latvian and English in WNT’17 News translation task. We also participated in the Biomedical task and produces translation engines from English into Polish, Czech, German, Spanish, French, Hungarian, Romanian and Swedish. To accomplish this, we performed …...

We describe the Sogou neural machine translation systems for the WMT 2017 Chinese↔English news translation tasks. Our systems are based on a multi- layer encoder-decoder architecture with attention mechanism. The best translation is obtained with ensemble and reranking techniques. We also pro- pose an approach to improve the named entity …...

We describe the JAIST phrase-based ma- chine translation systems that participated in the news translation shared task of the WMT17. In this work, we participated in the Turkish-English translation, in which only a small amount of bilingual training data is available, so that it is an exam- ple of the …...

The paper describes Tilde’s English- Latvian and Latvian-English machine translation systems for the WMT 2017 shared task in news translation. Both con- strained and unconstrained systems are de- scribed. Our constrained systems were ranked as the best performing systems ac- cording to the automatic evaluation re- sults. The paper gives …...

This paper describes the neural machine translation systems of the University of Latvia, University of Zurich and Univer- sity of Tartu. We participated in the WMT 2017 shared task on news translation by building systems for two language pairs: English↔German and English↔Latvian. Our systems are based on an attentional encoder-decoder, …...

This paper describes the statistical machine translation system developed at RWTH Aachen University for the English→German and German→English translation tasks of the EMNLP 2017 Second Conference on Machine Transla- tion (WMT 2017). We use ensembles of attention-based neural machine translation system for both directions. We use the provided parallel and …...

This paper describes the joint submis- sion of the QT21 projects for the English→Latvian translation task of the EMNLP 2017 Second Conference on Ma- chine Translation (WMT 2017). The sub- mission is a system combination which combines seven different statistical ma- chine translation systems provided by the different groups. The …...

This paper describes the Neural Machine Translation systems of Xiamen University for the translation tasks of WMT 17. Our systems are based on the Encoder-Decoder framework with attention. We partici- pated in three directions of shared news translation tasks: English→German and Chinese↔English. We experimented with deep architectures, different segmentation models, …...

We describe the machine translation sys- tems developed at the National Research Council of Canada (NRC) for the Russian- English and Chinese-English news trans- lation tasks of the Second Conference on Machine Translation (WMT 2017). We conducted several experiments to explore the best baseline settings for neural ma- chine translation …...

We introduce the Helsinki Neural Machine Translation system (HNMT) and how it is applied in the news translation task at WMT 2017, where it ranked first in both the human and automatic evaluations for English–Finnish. We discuss the success of English–Finnish translations and the overall advantage of NMT over a …...

The paper describes a rule-based machine translation system adapted to English to Finnish translation. Although the translation system participates in the shared task of news transla- tion in WMT 2017, the paper describes the strengths and weaknesses of the approach in general. 1 Credits We are grateful to Pasi Tapanainen …...

This paper describes the LMU Mu- nich English→German machine transla- tion 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 compet- itive machine translation quality on both news articles and …...

We present our experiments in the scope of the news translation task in WMT 2017, in three directions: German→English, English→German and English→Latvian. The core of our systems is the encoder- decoder based neural machine translation models , enhanced with various modeling features, additional source side augmen- tation and output rescoring. …...

We describe the neural machine trans- lation system submitted by the Univer- sity of Rochester to the Chinese-English language pair for the WMT 2017 news translation task. We applied unsuper- vised word and subword segmentation techniques and deep learning in order to address (i) the word segmentation prob- lem caused …...

This paper describes the University of Edinburgh’s submissions to the WMT17 shared news translation and biomedical translation tasks. We participated in 12 translation directions for news, translating between English and Czech, German, Lat- vian, Russian, Turkish and Chinese. For the biomedical task we submitted systems for English to Czech, German, …...

This paper describes LIUM submis- sions to WMT17 News Translation Task for English↔German, English↔Turkish, English→Czech and English→Latvian language pairs. We train BPE-based at- tentive Neural Machine Translation sys- tems with and without factored outputs using the open source nmtpy framework. Competitive scores were obtained by en- sembling various systems and …...

This article describes the Aalto University entry to the English-to-Finnish news trans- lation shared task in WMT 2017. Our sys- tem is an open vocabulary neural machine translation (NMT) system, adapted to the needs of a morphologically complex target language. The main contributions of this paper are 1) implicitly incorporating …...