Mercedes García-Martínez

Also published as: Mercedes García Martínez


2020

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Eco.pangeamt: Industrializing Neural MT
Mercedes García-Martínez | Manuel Herranz | Amando Estela | Ángela Franco | Laurent Bié
Proceedings of the 1st International Workshop on Language Technology Platforms

Eco is Pangeanic’s customer portal for generic or specialized translation services (machine translation and post-editing, generic API MT and custom API MT). Users can request the processing (translation) of files in different formats. Moreover, a client user can manage the engines and models allowing their cloning and retraining.

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A User Study of the Incremental Learning in NMT
Miguel Domingo | Mercedes García-Martínez | Álvaro Peris | Alexandre Helle | Amando Estela | Laurent Bié | Francisco Casacuberta | Manuel Herranz
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation

In the translation industry, human experts usually supervise and post-edit machine translation hypotheses. Adaptive neural machine translation systems, able to incrementally update the underlying models under an online learning regime, have been proven to be useful to improve the efficiency of this workflow. However, this incremental adaptation is somewhat unstable, and it may lead to undesirable side effects. One of them is the sporadic appearance of made-up words, as a byproduct of an erroneous application of subword segmentation techniques. In this work, we extend previous studies on on-the-fly adaptation of neural machine translation systems. We perform a user study involving professional, experienced post-editors, delving deeper on the aforementioned problems. Results show that adaptive systems were able to learn how to generate the correct translation for task-specific terms, resulting in an improvement of the user’s productivity. We also observed a close similitude, in terms of morphology, between made-up words and the words that were expected.

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The Multilingual Anonymisation Toolkit for Public Administrations (MAPA) Project
Ēriks Ajausks | Victoria Arranz | Laurent Bié | Aleix Cerdà-i-Cucó | Khalid Choukri | Montse Cuadros | Hans Degroote | Amando Estela | Thierry Etchegoyhen | Mercedes García-Martínez | Aitor García-Pablos | Manuel Herranz | Alejandro Kohan | Maite Melero | Mike Rosner | Roberts Rozis | Patrick Paroubek | Artūrs Vasiļevskis | Pierre Zweigenbaum
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation

We 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.

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Neural Translation for the European Union (NTEU) Project
Laurent Bié | Aleix Cerdà-i-Cucó | Hans Degroote | Amando Estela | Mercedes García-Martínez | Manuel Herranz | Alejandro Kohan | Maite Melero | Tony O’Dowd | Sinéad O’Gorman | Mārcis Pinnis | Roberts Rozis | Riccardo Superbo | Artūrs Vasiļevskis
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation

The Neural Translation for the European Union (NTEU) project aims to build a neural engine farm with all European official language combinations for eTranslation, without the necessity to use a high-resourced language as a pivot. NTEU started in September 2019 and will run until August 2021.

2019

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Demonstration of a Neural Machine Translation System with Online Learning for Translators
Miguel Domingo | Mercedes García-Martínez | Amando Estela Pastor | Laurent Bié | Alexander Helle | Álvaro Peris | Francisco Casacuberta | Manuel Herranz Pérez
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

We present a demonstration of our system, which implements online learning for neural machine translation in a production environment. These techniques allow the system to continuously learn from the corrections provided by the translators. We implemented an end-to-end platform integrating our machine translation servers to one of the most common user interfaces for professional translators: SDL Trados Studio. We pretend to save post-editing effort as the machine is continuously learning from its mistakes and adapting the models to a specific domain or user style.

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iADAATPA Project: Pangeanic use cases
Mercedes García-Martínez | Amando Estela | Laurent Bié | Alexandre Helle | Manuel Herranz
Proceedings of Machine Translation Summit XVII Volume 2: Translator, Project and User Tracks

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Incremental Adaptation of NMT for Professional Post-editors: A User Study
Miguel Domingo | Mercedes García-Martínez | Álvaro Peris | Alexandre Helle | Amando Estela | Laurent Bié | Francisco Casacuberta | Manuel Herranz
Proceedings of Machine Translation Summit XVII Volume 2: Translator, Project and User Tracks

2017

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Word Representations in Factored Neural Machine Translation
Franck Burlot | Mercedes García-Martínez | Loïc Barrault | Fethi Bougares | François Yvon
Proceedings of the Second Conference on Machine Translation

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LIUM Machine Translation Systems for WMT17 News Translation Task
Mercedes García-Martínez | Ozan Caglayan | Walid Aransa | Adrien Bardet | Fethi Bougares | Loïc Barrault
Proceedings of the Second Conference on Machine Translation

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LIUM-CVC Submissions for WMT17 Multimodal Translation Task
Ozan Caglayan | Walid Aransa | Adrien Bardet | Mercedes García-Martínez | Fethi Bougares | Loïc Barrault | Marc Masana | Luis Herranz | Joost van de Weijer
Proceedings of the Second Conference on Machine Translation

2016

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Does Multimodality Help Human and Machine for Translation and Image Captioning?
Ozan Caglayan | Walid Aransa | Yaxing Wang | Marc Masana | Mercedes García-Martínez | Fethi Bougares | Loïc Barrault | Joost van de Weijer
Proceedings of the First Conference on Machine Translation: Volume 2, Shared Task Papers

2014

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CASMACAT: A Computer-assisted Translation Workbench
Vicent Alabau | Christian Buck | Michael Carl | Francisco Casacuberta | Mercedes García-Martínez | Ulrich Germann | Jesús González-Rubio | Robin Hill | Philipp Koehn | Luis Leiva | Bartolomé Mesa-Lao | Daniel Ortiz-Martínez | Herve Saint-Amand | Germán Sanchis Trilles | Chara Tsoukala
Proceedings of the Demonstrations at the 14th Conference of the European Chapter of the Association for Computational Linguistics

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SEECAT: ASR & Eye-tracking enabled computer-assisted translation
Mercedes García-Martínez | Karan Singla | Aniruddha Tammewar | Bartolomé Mesa-Lao | Ankita Thakur | Anusuya M.A. | Srinivas Bangalore | Michael Carl
Proceedings of the 17th Annual conference of the European Association for Machine Translation

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Evaluating the effects of interactivity in a post-editing workbench
Nancy Underwood | Bartolomé Mesa-Lao | Mercedes García Martínez | Michael Carl | Vicent Alabau | Jesús González-Rubio | Luis A. Leiva | Germán Sanchis-Trilles | Daniel Ortíz-Martínez | Francisco Casacuberta
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

This paper describes the field trial and subsequent evaluation of a post-editing workbench which is currently under development in the EU-funded CasMaCat project. Based on user evaluations of the initial prototype of the workbench, this second prototype of the workbench includes a number of interactive features designed to improve productivity and user satisfaction. Using CasMaCat’s own facilities for logging keystrokes and eye tracking, data were collected from nine post-editors in a professional setting. These data were then used to investigate the effects of the interactive features on productivity, quality, user satisfaction and cognitive load as reflected in the post-editors’ gaze activity. These quantitative results are combined with the qualitative results derived from user questionnaires and interviews conducted with all the participants.