Gema Ramírez‐Sánchez

Also published as: Gema Ramirez-Sánchez, Gema Ramírez, Gema Ramírez Sánchez, Gema Ramírez-Sànchez, Gema Ramírez-Sánchez


2022

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Human evaluation of web-crawled parallel corpora for machine translation
Gema Ramírez-Sánchez | Marta Bañón | Jaume Zaragoza-Bernabeu | Sergio Ortiz Rojas
Proceedings of the 2nd Workshop on Human Evaluation of NLP Systems (HumEval)

Quality assessment has been an ongoing activity of the series of ParaCrawl efforts to crawl massive amounts of parallel data from multilingual websites for 29 languages. The goal of ParaCrawl is to get parallel data that is good for machine translation. To prove so, both, automatic (extrinsic) and human (intrinsic and extrinsic) evaluation tasks have been included as part of the quality assessment activity of the project. We sum up the various methods followed to address these evaluation tasks for the web-crawled corpora produced and their results. We review their advantages and disadvantages for the final goal of the ParaCrawl project and the related ongoing project MaCoCu.

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MultitraiNMT Erasmus+ project: Machine Translation Training for multilingual citizens (multitrainmt.eu)
Mikel L. Forcada | Pilar Sánchez-Gijón | Dorothy Kenny | Felipe Sánchez-Martínez | Juan Antonio Pérez Ortiz | Riccardo Superbo | Gema Ramírez Sánchez | Olga Torres-Hostench | Caroline Rossi
Proceedings of the 23rd Annual Conference of the European Association for Machine Translation

The MultitraiNMT Erasmus+ project has developed an open innovative syl-labus in machine translation, focusing on neural machine translation (NMT) and targeting both language learners and translators. The training materials include an open access coursebook with more than 250 activities and a pedagogical NMT interface called MutNMT that allows users to learn how neural machine translation works. These materials will allow students to develop the technical and ethical skills and competences required to become informed, critical users of machine translation in their own language learn-ing and translation practice. The pro-ject started in July 2019 and it will end in July 2022.

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MaCoCu: Massive collection and curation of monolingual and bilingual data: focus on under-resourced languages
Marta Bañón | Miquel Esplà-Gomis | Mikel L. Forcada | Cristian García-Romero | Taja Kuzman | Nikola Ljubešić | Rik van Noord | Leopoldo Pla Sempere | Gema Ramírez-Sánchez | Peter Rupnik | Vít Suchomel | Antonio Toral | Tobias van der Werff | Jaume Zaragoza
Proceedings of the 23rd Annual Conference of the European Association for Machine Translation

We introduce the project “MaCoCu: Massive collection and curation of monolingual and bilingual data: focus on under-resourced languages”, funded by the Connecting Europe Facility, which is aimed at building monolingual and parallel corpora for under-resourced European languages. The approach followed consists of crawling large amounts of textual data from carefully selected top-level domains of the Internet, and then applying a curation and enrichment pipeline. In addition to corpora, the project will release successive versions of the free/open-source web crawling and curation software used.

2021

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MultiTraiNMT: Training Materials to Approach Neural Machine Translation from Scratch
Gema Ramírez-Sánchez | Juan Antonio Pérez-Ortiz | Felipe Sánchez-Martínez | Caroline Rossi | Dorothy Kenny | Riccardo Superbo | Pilar Sánchez-Gijón | Olga Torres-Hostench
Proceedings of the Translation and Interpreting Technology Online Conference

The MultiTraiNMT Erasmus+ project aims at developing an open innovative syllabus in neural machine translation (NMT) for language learners and translators as multilingual citizens. Machine translation is seen as a resource that can support citizens in their attempt to acquire and develop language skills if they are trained in an informed and critical way. Machine translation could thus help tackle the mismatch between the desired EU aim of having multilingual citizens who speak at least two foreign languages and the current situation in which citizens generally fall far short of this objective. The training materials consists of an open-access coursebook, an open-source NMT web application called MutNMT for training purposes, and corresponding activities.

2020

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ParaCrawl: Web-Scale Acquisition of Parallel Corpora
Marta Bañón | Pinzhen Chen | Barry Haddow | Kenneth Heafield | Hieu Hoang | Miquel Esplà-Gomis | Mikel L. Forcada | Amir Kamran | Faheem Kirefu | Philipp Koehn | Sergio Ortiz Rojas | Leopoldo Pla Sempere | Gema Ramírez-Sánchez | Elsa Sarrías | Marek Strelec | Brian Thompson | William Waites | Dion Wiggins | Jaume Zaragoza
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

We report on methods to create the largest publicly available parallel corpora by crawling the web, using open source software. We empirically compare alternative methods and publish benchmark data sets for sentence alignment and sentence pair filtering. We also describe the parallel corpora released and evaluate their quality and their usefulness to create machine translation systems.

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Bifixer and Bicleaner: two open-source tools to clean your parallel data
Gema Ramírez-Sánchez | Jaume Zaragoza-Bernabeu | Marta Bañón | Sergio Ortiz Rojas
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation

This paper shows the utility of two open-source tools designed for parallel data cleaning: Bifixer and Bicleaner. Already used to clean highly noisy parallel content from crawled multilingual websites, we evaluate their performance in a different scenario: cleaning publicly available corpora commonly used to train machine translation systems. We choose four English–Portuguese corpora which we plan to use internally to compute paraphrases at a later stage. We clean the four corpora using both tools, which are described in detail, and analyse the effect of some of the cleaning steps on them. We then compare machine translation training times and quality before and after cleaning these corpora, showing a positive impact particularly for the noisiest ones.

2019

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ParaCrawl: Web-scale parallel corpora for the languages of the EU
Miquel Esplà | Mikel Forcada | Gema Ramírez-Sánchez | Hieu Hoang
Proceedings of Machine Translation Summit XVII: Translator, Project and User Tracks

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Large-scale Machine Translation Evaluation of the iADAATPA Project
Sheila Castilho | Natália Resende | Federico Gaspari | Andy Way | Tony O’Dowd | Marek Mazur | Manuel Herranz | Alex Helle | Gema Ramírez-Sánchez | Víctor Sánchez-Cartagena | Mārcis Pinnis | Valters Šics
Proceedings of Machine Translation Summit XVII: Translator, Project and User Tracks

2018

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Same-language machine translation for local flavours/flavors
Gema Ramírez-Sánchez | Janice Campbell
Proceedings of the 13th Conference of the Association for Machine Translation in the Americas (Volume 2: User Track)

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Prompsit’s submission to WMT 2018 Parallel Corpus Filtering shared task
Víctor M. Sánchez-Cartagena | Marta Bañón | Sergio Ortiz-Rojas | Gema Ramírez
Proceedings of the Third Conference on Machine Translation: Shared Task Papers

This paper describes Prompsit Language Engineering’s submissions to the WMT 2018 parallel corpus filtering shared task. Our four submissions were based on an automatic classifier for identifying pairs of sentences that are mutual translations. A set of hand-crafted hard rules for discarding sentences with evident flaws were applied before the classifier. We explored different strategies for achieving a training corpus with diverse vocabulary and fluent sentences: language model scoring, an active-learning-inspired data selection algorithm and n-gram saturation. Our submissions were very competitive in comparison with other participants on the 100 million word training corpus.

2016

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Collaborative Development of a Rule-Based Machine Translator between Croatian and Serbian
Filip Klubička | Gema Ramírez-Sánchez | Nikola Ljubešić
Proceedings of the 19th Annual Conference of the European Association for Machine Translation

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Re-assessing the Impact of SMT Techniques with Human Evaluation: a Case Study on English—Croatian
Antonio Toral | Raphael Rubino | Gema Ramírez-Sánchez
Proceedings of the 19th Annual Conference of the European Association for Machine Translation

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AltLang: an automatic converter between varieties of English, Spanish, French and Portuguese
Gema Ramírez-Sànchez
Proceedings of the 19th Annual Conference of the European Association for Machine Translation: Projects/Products

2015

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Proceedings of the 18th Annual Conference of the European Association for Machine Translation
İIknur El‐Kahlout | Mehmed Özkan | Felipe Sánchez‐Martínez | Gema Ramírez‐Sánchez | Fred Hollywood | Andy Way
Proceedings of the 18th Annual Conference of the European Association for Machine Translation

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Abu-MaTran: Automatic building of Machine Translation
Antonio Toral | Tommi A Pirinen | Andy Way | Gema Ramírez-Sánchez | Sergio Ortiz Rojas | Raphael Rubino | Miquel Esplà | Mikel Forcada | Vassilis Papavassiliou | Prokopis Prokopidis | Nikola Ljubešić
Proceedings of the 18th Annual Conference of the European Association for Machine Translation

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Proceedings of the 18th Annual Conference of the European Association for Machine Translation
İlknur Durgar El-Kahlout | Mehmed Özkan | Felipe Sánchez-Martínez | Gema Ramírez-Sánchez | Fred Hollowood | Andy Way
Proceedings of the 18th Annual Conference of the European Association for Machine Translation

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Abu-MaTran: Automatic building of Machine Translation
Antonio Toral | Tommi A. Pirinen | Andy Way | Gema Ramírez-Sánchez | Sergio Ortiz Rojas | Raphael Rubino | Miquel Esplà | Mikel L. Forcada | Vassilis Papavassiliou | Prokopis Prokopidis | Nikola Ljubešić
Proceedings of the 18th Annual Conference of the European Association for Machine Translation

2014

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Abu-MaTran at WMT 2014 Translation Task: Two-step Data Selection and RBMT-Style Synthetic Rules
Raphael Rubino | Antonio Toral | Victor M. Sánchez-Cartagena | Jorge Ferrández-Tordera | Sergio Ortiz-Rojas | Gema Ramírez-Sánchez | Felipe Sánchez-Martínez | Andy Way
Proceedings of the Ninth Workshop on Statistical Machine Translation

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Quality Estimation for Synthetic Parallel Data Generation
Raphael Rubino | Antonio Toral | Nikola Ljubešić | Gema Ramírez-Sánchez
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

This paper presents a novel approach for parallel data generation using machine translation and quality estimation. Our study focuses on pivot-based machine translation from English to Croatian through Slovene. We generate an English―Croatian version of the Europarl parallel corpus based on the English―Slovene Europarl corpus and the Apertium rule-based translation system for Slovene―Croatian. These experiments are to be considered as a first step towards the generation of reliable synthetic parallel data for under-resourced languages. We first collect small amounts of aligned parallel data for the Slovene―Croatian language pair in order to build a quality estimation system for sentence-level Translation Edit Rate (TER) estimation. We then infer TER scores on automatically translated Slovene to Croatian sentences and use the best translations to build an English―Croatian statistical MT system. We show significant improvement in terms of automatic metrics obtained on two test sets using our approach compared to a random selection of synthetic parallel data.

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Extrinsic evaluation of web-crawlers in machine translation: a study on Croatian-English for the tourism domain
Antonio Toral | Raphael Rubino | Miquel Esplà-Gomis | Tommi Pirinen | Andy Way | Gema Ramírez-Sánchez
Proceedings of the 17th Annual conference of the European Association for Machine Translation

2012

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Opinum: statistical sentiment analysis for opinion classification
Boyan Bonev | Gema Ramírez-Sánchez | Sergio Ortiz Rojas
Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis

2010

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Using the Apertium Spanish-Brazilian Portuguese machine translation system for localization
François Masselot | Petra Ribiczey | Gema Ramírez-Sánchez
Proceedings of the 14th Annual conference of the European Association for Machine Translation

2009

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The Apertium machine translation platform: Five years on
Mikel L. Forcada | Francis M. Tyers | Gema Ramírez-Sánchez
Proceedings of the First International Workshop on Free/Open-Source Rule-Based Machine Translation

This paper describes Apertium: a free/open-source machine translation platform (engine, toolbox and data), its history, its philosophy of design, its technology, the community of developers, the research and business based on it, and its prospects and challenges, now that it is five years old.

2006

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Opentrad Apertium Open-Source Machine Translation System: an Opportunity for Business and Research
Gema Ramirez-Sánchez
Proceedings of Translating and the Computer 28

2005

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An Open-Source Shallow-Transfer Machine Translation Toolbox: Consequences of Its Release and Availability
Carme Armentano-Oller | Antonio M. Corbí-Bellot | Mikel L. Forcada | Mireia Ginestí-Rosell | Boyan Bonev | Sergio Ortiz-Rojas | Juan Antonio Pérez-Ortiz | Gema Ramírez-Sánchez | Felipe Sánchez-Martínez
Workshop on open-source machine translation

By the time Machine Translation Summit X is held in September 2005, our group will have released an open-source machine translation toolbox as part of a large government-funded project involving four universities and three linguistic technology companies from Spain. The machine translation toolbox, which will most likely be released under a GPL-like license includes (a) the open-source engine itself, a modular shallow-transfer machine translation engine suitable for related languages and largely based upon that of systems we have already developed, such as interNOSTRUM for Spanish—Catalan and Traductor Universia for Spanish—Portuguese, (b) extensive documentation (including document type declarations) specifying the XML format of all linguistic (dictionaries, rules) and document format management files, (c) compilers converting these data into the high-speed (tens of thousands of words a second) format used by the engine, and (d) pilot linguistic data for Spanish—Catalan and Spanish—Galician and format management specifications for the HTML, RTF and plain text formats. After describing very briefly this toolbox, this paper aims at exploring possible consequences of the availability of this architecture, including the community-driven development of machine translation systems for languages lacking this kind of linguistic technology.

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An open-source shallow-transfer machine translation engine for the Romance languages of Spain
Antonio M. Corbi-Bellot | Mikel L. Forcada | Sergio Ortíz-Rojas | Juan Antonio Pérez-Ortiz | Gema Ramírez-Sánchez | Felipe Sánchez-Martínez | Iñaki Alegria | Aingeru Mayor | Kepa Sarasola
Proceedings of the 10th EAMT Conference: Practical applications of machine translation