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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 15 of 15 1 Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach Sánchez-Cartagena, Víctor M.; Sánchez-Martínez, Felipe; Pérez-Ortiz, Juan Antonio. - : Association for Computational Linguistics, 2021 BASE Show details 2 Understanding the effects of word-level linguistic annotations in under-resourced neural machine translation Sánchez-Cartagena, Víctor M.; Pérez-Ortiz, Juan Antonio; Sánchez-Martínez, Felipe. - : Association for Computational Linguistics, 2020 BASE Show details 3 The Universitat d'Alacant submissions to the English-to-Kazakh news translation task at WMT 2019 ... Sánchez-Cartagena, Víctor M.; Pérez-Ortiz, Juan Antonio; Sánchez-Martínez, Felipe. - : Zenodo, 2019 BASE Show details 4 The Universitat d'Alacant submissions to the English-to-Kazakh news translation task at WMT 2019 ... Sánchez-Cartagena, Víctor M.; Pérez-Ortiz, Juan Antonio; Sánchez-Martínez, Felipe. - : Zenodo, 2019 BASE Show details 5 Assisting non-expert speakers of under-resourced languages in assigning stems and inflectional paradigms to new word entries of morphological dictionaries Forcada, Mikel L.; Carrasco, Rafael C.; Pérez-Ortiz, Juan Antonio. - : Springer Science+Business Media Dordrecht, 2017 BASE Show details 6 Integrating Rules and Dictionaries from Shallow-Transfer Machine Translation into Phrase-Based Statistical Machine Translation Sánchez-Cartagena, Víctor M.; Pérez-Ortiz, Juan Antonio; Sánchez-Martínez, Felipe. - : AI Access Foundation, 2016 BASE Show details 7 RuLearn: an Open-source Toolkit for the Automatic Inference of Shallow-transfer Rules for Machine Translation Pérez-Ortiz, Juan Antonio; Sánchez-Cartagena, Víctor M.; Sánchez-Martínez, Felipe. - : De Gruyter, 2016 Abstract: This paper presents ruLearn, an open-source toolkit for the automatic inference of rules for shallow-transfer machine translation from scarce parallel corpora and morphological dictionaries. ruLearn will make rule-based machine translation a very appealing alternative for under-resourced language pairs because it avoids the need for human experts to handcraft transfer rules and requires, in contrast to statistical machine translation, a small amount of parallel corpora (a few hundred parallel sentences proved to be sufficient). The inference algorithm implemented by ruLearn has been recently published by the same authors in Computer Speech & Language (volume 32). It is able to produce rules whose translation quality is similar to that obtained by using hand-crafted rules. ruLearn generates rules that are ready for their use in the Apertium platform, although they can be easily adapted to other platforms. When the rules produced by ruLearn are used together with a hybridisation strategy for integrating linguistic resources from shallow-transfer rule-based machine translation into phrase-based statistical machine translation (published by the same authors in Journal of Artificial Intelligence Research, volume 55), they help to mitigate data sparseness. This paper also shows how to use ruLearn and describes its implementation. ; Research funded by the Spanish Ministry of Economy and Competitiveness through projects TIN2009-14009-C02-01 and TIN2012-32615, by Generalitat Valenciana through grant ACIF/2010/174, and by the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement PIAP-GA-2012-324414 (Abu-MaTran). Keyword: Automatic inference; Lenguajes y Sistemas Informáticos; Machine translation; ruLearn; Shallow-transfer rules URL: http://hdl.handle.net/10045/60039 https://doi.org/10.1515/pralin-2016-0018 BASE Hide details 8 A generalised alignment template formalism and its application to the inference of shallow-transfer machine translation rules from scarce bilingual corpora Sánchez-Cartagena, Víctor M.; Pérez-Ortiz, Juan Antonio; Sánchez-Martínez, Felipe. - : Elsevier, 2015 BASE Show details 9 An open-source toolkit for integrating shallow-transfer rules into phrase-based statistical machine translation Sánchez-Cartagena, Víctor M.; Sánchez-Martínez, Felipe; Pérez-Ortiz, Juan Antonio. - : CSLI Publications, 2012 BASE Show details 10 Choosing the correct paradigm for unknown words in rule-based machine translation systems Sánchez-Cartagena, Víctor M.; Esplà-Gomis, Miquel; Sánchez-Martínez, Felipe. - : CSLI Publications, 2012 BASE Show details 11 The Universitat d’Alacant hybrid machine translation system for WMT 2011 Sánchez-Cartagena, Víctor M.; Sánchez-Martínez, Felipe; Pérez-Ortiz, Juan Antonio. - : Association for Computational Linguistics, 2011 BASE Show details 12 Integrating shallow-transfer rules into phrase-based statistical machine translation Sánchez-Cartagena, Víctor M.; Sánchez-Martínez, Felipe; Pérez-Ortiz, Juan Antonio. - : Machine Translation Summit, 2011 BASE Show details 13 Enriching a statistical machine translation system trained on small parallel corpora with rule-based bilingual phrases Sánchez-Cartagena, Víctor M.; Sánchez-Martínez, Felipe; Pérez-Ortiz, Juan Antonio. - : RANLP, 2011 BASE Show details 14 ScaleMT: a free/open-source framework for building scalable machine translation web services Sánchez-Cartagena, Víctor M.; Pérez-Ortiz, Juan Antonio. - : Charles University in Prague. Institute of Formal and Applied Linguistics, 2009. : Versita, 2009 BASE Show details 15 Tradubi: open-source social translation for the Apertium machine translation platform Sánchez-Cartagena, Víctor M.; Pérez-Ortiz, Juan Antonio. - : Charles University in Prague. Institute of Formal and Applied Linguistics, 2009. : Versita, 2009 BASE Show details

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