Federico Gaspari


2020

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ELRI: A Decentralised Network of National Relay Stations to Collect, Prepare and Share Language Resources
Thierry Etchegoyhen | Borja Anza Porras | Andoni Azpeitia | Eva Martínez Garcia | José Luis Fonseca | Patricia Fonseca | Paulo Vale | Jane Dunne | Federico Gaspari | Teresa Lynn | Helen McHugh | Andy Way | Victoria Arranz | Khalid Choukri | Hervé Pusset | Alexandre Sicard | Rui Neto | Maite Melero | David Perez | António Branco | Ruben Branco | Luís Gomes
Proceedings of the 1st International Workshop on Language Technology Platforms

We describe the European Language Resource Infrastructure (ELRI), a decentralised network to help collect, prepare and share language resources. The infrastructure was developed within a project co-funded by the Connecting Europe Facility Programme of the European Union, and has been deployed in the four Member States participating in the project, namely France, Ireland, Portugal and Spain. ELRI provides sustainable and flexible means to collect and share language resources via National Relay Stations, to which members of public institutions can freely subscribe. The infrastructure includes fully automated data processing engines to facilitate the preparation, sharing and wider reuse of useful language resources that can help optimise human and automated translation services in the European Union.

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Progress of the PRINCIPLE Project: Promoting MT for Croatian, Icelandic, Irish and Norwegian
Andy Way | Petra Bago | Jane Dunne | Federico Gaspari | Andre Kåsen | Gauti Kristmannsson | Helen McHugh | Jon Arild Olsen | Dana Davis Sheridan | Páraic Sheridan | John Tinsley
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation

This 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 translation (MT) systems. We report initial achievements of the project and ongoing activities aimed at promoting the uptake of neural MT for the low-resource languages of the project.

2019

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Proceedings of Machine Translation Summit XVII Volume 2: Translator, Project and User Tracks
Mikel Forcada | Andy Way | John Tinsley | Dimitar Shterionov | Celia Rico | Federico Gaspari
Proceedings of Machine Translation Summit XVII Volume 2: Translator, Project and User Tracks

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PRINCIPLE: Providing Resources in Irish, Norwegian, Croatian and Icelandic for the Purposes of Language Engineering
Andy Way | Federico Gaspari
Proceedings of Machine Translation Summit XVII Volume 2: 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 Volume 2: Translator, Project and User Tracks

2018

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Improving Machine Translation of Educational Content via Crowdsourcing
Maximiliana Behnke | Antonio Valerio Miceli Barone | Rico Sennrich | Vilelmini Sosoni | Thanasis Naskos | Eirini Takoulidou | Maria Stasimioti | Menno van Zaanen | Sheila Castilho | Federico Gaspari | Panayota Georgakopoulou | Valia Kordoni | Markus Egg | Katia Lida Kermanidis
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2017

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Enhancing Machine Translation of Academic Course Catalogues with Terminological Resources
Randy Scansani | Silvia Bernardini | Adriano Ferraresi | Federico Gaspari | Marcello Soffritti
Proceedings of the Workshop Human-Informed Translation and Interpreting Technology

This paper describes an approach to translating course unit descriptions from Italian and German into English, using a phrase-based machine translation (MT) system. The genre is very prominent among those requiring translation by universities in European countries in which English is a non-native language. For each language combination, an in-domain bilingual corpus including course unit and degree program descriptions is used to train an MT engine, whose output is then compared to a baseline engine trained on the Europarl corpus. In a subsequent experiment, a bilingual terminology database is added to the training sets in both engines and its impact on the output quality is evaluated based on BLEU and post-editing score. Results suggest that the use of domain-specific corpora boosts the engines quality for both language combinations, especially for German-English, whereas adding terminological resources does not seem to bring notable benefits.

2016

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Enhancing Cross-border EU E-commerce through Machine Translation: Needed Language Resources, Challenges and Opportunities
Meritxell Fernández Barrera | Vladimir Popescu | Antonio Toral | Federico Gaspari | Khalid Choukri
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

This paper discusses the role that statistical machine translation (SMT) can play in the development of cross-border EU e-commerce,by highlighting extant obstacles and identifying relevant technologies to overcome them. In this sense, it firstly proposes a typology of e-commerce static and dynamic textual genres and it identifies those that may be more successfully targeted by SMT. The specific challenges concerning the automatic translation of user-generated content are discussed in detail. Secondly, the paper highlights the risk of data sparsity inherent to e-commerce and it explores the state-of-the-art strategies to achieve domain adequacy via adaptation. Thirdly, it proposes a robust workflow for the development of SMT systems adapted to the e-commerce domain by relying on inexpensive methods. Given the scarcity of user-generated language corpora for most language pairs, the paper proposes to obtain monolingual target-language data to train language models and aligned parallel corpora to tune and evaluate MT systems by means of crowdsourcing.

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TraMOOC (Translation for Massive Open Online Courses): providing reliable MT for MOOCs
Valia Kordoni | Lexi Birch | Ioana Buliga | Kostadin Cholakov | Markus Egg | Federico Gaspari | Yota Georgakopolou | Maria Gialama | Iris Hendrickx | Mitja Jermol | Katia Kermanidis | Joss Moorkens | Davor Orlic | Michael Papadopoulos | Maja Popović | Rico Sennrich | Vilelmini Sosoni | Dimitrios Tsoumakos | Antal van den Bosch | Menno van Zaanen | Andy Way
Proceedings of the 19th Annual Conference of the European Association for Machine Translation: Projects/Products

2013

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A Web Application for the Diagnostic Evaluation of Machine Translation over Specific Linguistic Phenomena
Antonio Toral | Sudip Kumar Naskar | Joris Vreeke | Federico Gaspari | Declan Groves
Proceedings of the 2013 NAACL HLT Demonstration Session

2011

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A Comparative Evaluation of Research vs. Online MT Systems
Antonio Toral | Federico Gaspari | Sudip Kumar Naskar | Andy Way
Proceedings of the 15th Annual conference of the European Association for Machine Translation

2006

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Detecting Inappropriate Use of Free Online Machine Translation by Language Students. A Special Case of Plagiarism Detection
Harold Somers | Federico Gaspari | Ana Niño
Proceedings of the 11th Annual conference of the European Association for Machine Translation

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Look Who’s Translating. Impersonations, Chinese Whispers and Fun with Machine Translation on the Internet
Federico Gaspari
Proceedings of the 11th Annual conference of the European Association for Machine Translation

2004

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Integrating on-line MT services into monolingual web-sites for dissemination purposes: an evaluation perspective
Federico Gaspari
Proceedings of the 9th EAMT Workshop: Broadening horizons of machine translation and its applications

2002

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Using free on-line services in MT training
Federico Gaspari
Proceedings of the 6th EAMT Workshop: Teaching Machine Translation