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Moses: Open Source Toolkit for Statistical Machine Translation
TLDR
We describe an open-source toolkit for statistical machine translation whose novel contributions are (a) support for linguistically motivated factors, (b) confusion network decoding, and efficient data formats for translation models and language models. Expand
Neural Machine Translation of Rare Words with Subword Units
TLDR
In this paper, we introduce a simpler and more effective approach, making the NMT model capable of open-vocabulary translation by encoding rare and unknown words as sequences of subword units. Expand
Improving Neural Machine Translation Models with Monolingual Data
TLDR
Neural Machine Translation (NMT) has obtained state-of-the art performance for several language pairs, while only using parallel data for training. Expand
Edinburgh Neural Machine Translation Systems for WMT 16
TLDR
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. Expand
Nematus: a Toolkit for Neural Machine Translation
We present Nematus, a toolkit for Neural Machine Translation. The toolkit prioritizes high translation accuracy, usability, and extensibility. Nematus has been used to build top-performingExpand
Controlling Politeness in Neural Machine Translation via Side Constraints
TLDR
We propose a simple and effective method for including target-side T-V annotation in the training of a neural machine translation (NMT) system, which allows us to control the level of politeness at test time through side constraints. Expand
Edinburgh system description for the 2005 IWSLT speech translation evaluation
TLDR
We adapted our statistical machine translation system that performed successfully in previous DARPA competitions on open domain text translations to the limited domain speech translation task. Expand
Evaluating Discourse Phenomena in Neural Machine Translation
TLDR
In this article, we present hand-crafted, discourse test sets, designed to test the models' ability to exploit previous source and target sentences. Expand
Marian: Fast Neural Machine Translation in C++
TLDR
We present Marian, an efficient and self-contained Neural Machine Translation framework with an integrated automatic differentiation engine based on dynamic computation graphs. Expand
The University of Edinburgh's Neural MT Systems for WMT17
TLDR
This paper describes the University of Edinburgh's submissions to the WMT17 shared news translation and biomedical translation tasks. Expand
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