Mercè Vàzquez

Also published as: Merce Vazquez


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TAN-IBE: Neural Machine Translation for the romance languages of the Iberian Peninsula
Antoni Oliver | Mercè Vàzquez | Marta Coll-Florit | Sergi Álvarez | Víctor Suárez | Claudi Aventín-Boya | Cristina Valdés | Mar Font | Alejandro Pardos
Proceedings of the 24th Annual Conference of the European Association for Machine Translation

The main goal of this project is to explore the techniques for training NMT systems applied to Spanish, Portuguese, Catalan, Galician, Asturian, Aragonese and Aranese. These languages belong to the same Romance family, but they are very different in terms of the linguistic resources available. Asturian, Aragonese and Aranese can be considered low resource languages. These characteristics make this setting an excellent place to explore training techniques for low-resource languages: transfer learning and multilingual systems, among others. The first months of the project have been dedicated to the compilation of monolingual and parallel corpora for Asturian, Aragonese and Aranese.


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TermEval 2020: Using TSR Filtering Method to Improve Automatic Term Extraction
Antoni Oliver | Mercè Vàzquez
Proceedings of the 6th International Workshop on Computational Terminology

The identification of terms from domain-specific corpora using computational methods is a highly time-consuming task because terms has to be validated by specialists. In order to improve term candidate selection, we have developed the Token Slot Recognition (TSR) method, a filtering strategy based on terminological tokens which is used to rank extracted term candidates from domain-specific corpora. We have implemented this filtering strategy in TBXTools. In this paper we present the system we have used in the TermEval 2020 shared task on monolingual term extraction. We also present the evaluation results for the system for English, French and Dutch and for two corpora: corruption and heart failure. For English and French we have used a linguistic methodology based on POS patterns, and for Dutch we have used a statistical methodology based on n-grams calculation and filtering with stop-words. For all languages, TSR (Token Slot Recognition) filtering method has been applied. We have obtained competitive results, but there is still room for improvement of the system.


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TBXTools: A Free, Fast and Flexible Tool for Automatic Terminology Extraction
Antoni Oliver | Mercè Vàzquez
Proceedings of the International Conference Recent Advances in Natural Language Processing


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A free terminology extraction suite
Antoni Oliver | Merce Vazquez
Proceedings of Translating and the Computer 29