Articles

AbstractThe APE-QUEST project (2018–2020) sets up a quality gate and crowdsourcing workflow for the eTranslation system of EC’s Connecting Europe Facility to improve translation quality in specific domains. It packages these services as a translation portal for machine-to-machine and machine-to-human scenarios....

Word alignments identify translational correspondences between words in a parallel sentence pair and are used, for instance, to learn bilingual dictionaries, to train statistical machine trans- lation systems or to perform quality estimation. Variational autoencoders have been recently used in various of natural language processing to learn in an unsupervised …...

AbstractWe describe the MAPA project, funded under the Connecting Europe Facility programme, whose goal is the development of an open-source de-identification toolkit for all official European Union languages. It will be developed since January 2020 until December 2021....

AbstractIn this paper the MTUOC project, aiming to provide an easy integration of neural and statistical machine translation systems, is presented. Almost all the required software to train and use neural and statistical MT systems are released under free licences. However, their use is not always easy and intuitive and …...

AbstractThis paper updates the progress made on the PRINCIPLE project, a 2-year action funded by the European Commission under the Connecting Europe Facility (CEF) programme. PRINCIPLE focuses on collecting high-quality language resources for Croatian, Icelandic, Irish and Norwegian, which have been identified as low-resource languages, especially for building effective machine …...

AbstractELITR (European Live Translator) project aims to create a speech translation system for simultaneous subtitling of conferences and online meetings targetting up to 43 languages. The technology is tested by the Supreme Audit Office of the Czech Republic and by alfaview®, a German online conferencing system. Other project goals are …...

AbstractThis project aims to identify the important aspects of translation quality of user reviews which will represent a starting point for developing better automatic MT metrics and challenge test sets, and will be also helpful for developing MT systems for this genre. We work on two types of reviews: Amazon …...

AbstractWe present Sockeye 2, a modernized and streamlined version of the Sockeye neural machine translation (NMT) toolkit. New features include a simplified code base through the use of MXNet’s Gluon API, a focus on state of the art model architectures, and distributed mixed precision training. These improvements result in faster …...

AbstractDocument-level (doc-level) human eval-uation of machine translation (MT) has raised interest in the community after a fewattempts have disproved claims of “human parity” (Toral et al., 2018; Laubli et al.,2018). However, little is known about bestpractices regarding doc-level human evalu-ation. The goal of this project is to identifywhich methodologies better …...

AbstractINMIGRA3 is a three-year project that builds on the work of two previous initi-atives: INMIGRA2-CM and CRISIS-MT . Together, they address the specific needs of NGOs in multilingual settings with a particular interest in migratory contexts. Work on INMIGRA3 concentrates in the analysis of how best can be NMT put …...

AbstractQE Viewer is a web-based tool for visualizing results of a Machine Translation Quality Estimation (QE) system. It allows users to see information on the predicted post-editing distance (PED) for a given file or sentence, and highlighted words that were predicted to contain MT errors. The tool can be used …...

AbstractThe present study aims to compare three systems: a generic statistical machine translation (SMT), a generic neural machine translation (NMT) and a tailored-NMT system focusing on the English to Greek language pair. The comparison is carried out following a mixed-methods approach, i.e. automatic metrics, as well as side-by-side ranking, adequacy …...

AbstractWith official status in both Ireland and the EU, there is a need for high-quality English-Irish (EN-GA) machine translation (MT) systems which are suitable for use in a professional translation environment. While we have seen recent research on improving both statistical MT and neural MT for the EN-GA pair, the …...

AbstractThis article describes the results of a workshop in which 50 translators tested two experimental translation interfaces, as part of a project which aimed at studying the details of editing work. In this work, editing is defined as a selection of four actions: deleting, inserting, moving and replacing words. Four …...

Translating text that diverges from the training domain is a key challenge for machine trans- lation. Domain robustness—the generalization of models to unseen test domains—is low for both statistical (SMT) and neural machine translation (NMT). In this paper, we study the per- formance of SMT and NMT models on out-of-domain …...

Recent studies on direct speech translation show continuous improvements by means of data augmentation techniques and bigger deep learning models. While these methods are helping to close the gap between this new approach and the more traditional cascaded one, there are many incongruities among different studies that make it difficult …...

For spoken language translation (SLT) in live scenarios such as conferences, lectures and meet- ings, it is desirable to show the translation to the user as quickly as possible, avoiding an an- noying lag between speaker and translated captions. In other words, we would like low-latency, online SLT. If we …...

THUMT is an open-source toolkit for neural machine translation (NMT) developed by the Natural Language Processing Group at Tsinghua University. The toolkit is easy to use, mod- ify and extend while provides the latest advances in NMT research and production. THUMT implements several standard NMT models and supports distributed training …...

We present Sockeye 2, a modernized and streamlined version of the Sockeye neural machine translation (NMT) toolkit. New features include a simplified code base through the use of MXNet’s Gluon API, a focus on state of the art model architectures, distributed mixed precision training, and efficient CPU decoding with 8-bit …...

OpenNMT is a multi-year open-source ecosystem for neural machine translation (NMT) and natural language generation (NLG). The toolkit consists of multiple projects to cover the com- plete machine learning workflow: from data preparation to inference acceleration. The systems prioritize efficiency, modularity, and extensibility with the goal of supporting research into …...