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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
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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
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3
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
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4
Integrating Rules and Dictionaries from Shallow-Transfer Machine Translation into Phrase-Based Statistical Machine Translation
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5
RuLearn: an Open-source Toolkit for the Automatic Inference of Shallow-transfer Rules for Machine Translation
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6
A generalised alignment template formalism and its application to the inference of shallow-transfer machine translation rules from scarce bilingual corpora
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7
An open-source toolkit for integrating shallow-transfer rules into phrase-based statistical machine translation
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8
Choosing the correct paradigm for unknown words in rule-based machine translation systems
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9
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
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10
Integrating shallow-transfer rules into phrase-based statistical machine translation
Abstract: In this paper, we extensively evaluate a new hybridisation approach consisting of enriching the phrase table of a phrase-based statistical machine translation system with bilingual phrase pairs matching transfer rules and dictionary entries from a shallow-transfer rule-based machine translation system. The experiments conducted show an improvement in translation quality, specially when the parallel corpus available for training is small or when translating out-of-domain texts that are well covered by the shallow-transfer rule-based machine translation system. ; Work funded by the Spanish Ministry of Science and Innovation through project TIN2009-14009-C02-01 and by Generalitat Valenciana through grant ACIF/2010/174 (VALi+d programme).
Keyword: Lenguajes y Sistemas Informáticos; Machine translation; Phrase-based; Rule-based; Shallow-transfer; Statistical machine translation system
URL: http://hdl.handle.net/10045/27579
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11
Enriching a statistical machine translation system trained on small parallel corpora with rule-based bilingual phrases
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12
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
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13
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
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