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MultiTraiNMT: training materials to approach neural machine translation from scratch ; MultiTraiNMT: des outils pour se former à la traduction automatique neuronale
In: TRITON 2021 (Translation and Interpreting Technology Online) ; https://hal.archives-ouvertes.fr/hal-03272570 ; TRITON 2021 (Translation and Interpreting Technology Online), Jul 2021, Online, United Kingdom (2021)
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Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach ...
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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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Fuzzy-Match Repair in Computer-Aided Translation Using Black-Box Machine Translation
Ortega, John E.. - : Universidad de Alicante, 2021
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Understanding the effects of word-level linguistic annotations in under-resourced neural machine translation ...
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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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The Universitat d'Alacant submissions to the English-to-Kazakh news translation task at WMT 2019 ...
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The Universitat d'Alacant submissions to the English-to-Kazakh news translation task at WMT 2019 ...
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Reading comprehension of machine translation output: what makes for a better read?
In: Castilho, Sheila orcid:0000-0002-8416-6555 and Guerberof Arenas, Ana orcid:0000-0001-9820-7074 (2018) Reading comprehension of machine translation output: what makes for a better read? In: 21st Annual Conference of the European for Machine Translation, 28-30 May 2018, Alacant/Alicante, Spain. ISBN 978-84-09-01901-4 (2018)
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Predicting insertion positions in word-level machine translation quality estimation
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Towards Optimizing MT for Post-Editing Effort: Can BLEU Still Be Useful?
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Assisting non-expert speakers of under-resourced languages in assigning stems and inflectional paradigms to new word entries of morphological dictionaries
Abstract: This paper presents a new method with which to assist individuals with no background in linguistics to create monolingual dictionaries such as those used by the morphological analysers of many natural language processing applications. The involvement of non-expert users is especially critical for under-resourced languages which either lack or cannot afford the recruitment of a skilled workforce. Adding a word to a morphological dictionary usually requires identifying its stem along with the inflection paradigm that can be used in order to generate all the word forms of the new entry. Our method works under the assumption that the average speakers of a language can successfully answer the polar question “is x a valid form of the word w to be inserted?”, where x represents tentative alternative (inflected) forms of the new word w. The experiments show that with a small number of polar questions the correct stem and paradigm can be obtained from non-experts with high success rates. We study the impact of different heuristic and probabilistic approaches on the actual number of questions. ; This work has been partially funded by the Spanish Ministry of Science & Innovation through project TIN2009-14009-C02-01, by the Spanish Ministry of Economy & Competitiveness through Project TIN2012-32615, by the Generalitat Valenciana through grant ACIF/2010/174 from VALi+d programme, and by the European Commission through Project PIAP-GA-2012-324414 (Abu-MaTran).
Keyword: Enlargement of morphological dictionaries; Knowledge elicitation; Lenguajes y Sistemas Informáticos; Machine translation; Resource development for under-resourced languages
URL: http://hdl.handle.net/10045/71353
https://doi.org/10.1007/s10579-016-9360-9
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Towards Optimizing MT for Post-Editing Effort: Can BLEU Still Be Useful?
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 183-195 (2017) (2017)
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Integrating Rules and Dictionaries from Shallow-Transfer Machine Translation into Phrase-Based Statistical Machine Translation
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RuLearn: an Open-source Toolkit for the Automatic Inference of Shallow-transfer Rules for Machine Translation
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Phrase-based statistical machine translation: explanation of its processes and statistical models and evaluation of the English to Spanish translations produced
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Using external sources of bilingual information for word-level quality estimation in translation technologies
Esplà-Gomis, Miquel. - : Universidad de Alicante, 2016
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RuLearn: an Open-source Toolkit for the Automatic Inference of Shallow-transfer Rules for Machine Translation
In: Prague Bulletin of Mathematical Linguistics , Vol 106, Iss 1, Pp 193-204 (2016) (2016)
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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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Using Machine Translation to Provide Target-Language Edit Hints in Computer Aided Translation Based on Translation Memories
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