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Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach
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Understanding the effects of word-level linguistic annotations in under-resourced neural machine translation
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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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Quantitative Fine-Grained Human Evaluation of Machine Translation Systems: a Case Study on English to Croatian ...
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Fine-grained human evaluation of neural versus phrase-based machine translation ...
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A Multifaceted Evaluation of Neural versus Phrase-Based Machine Translation for 9 Language Directions ...
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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
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Fine-Grained Human Evaluation of Neural Versus Phrase-Based Machine Translation
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In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 121-132 (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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RuLearn: an Open-source Toolkit for the Automatic Inference of Shallow-transfer Rules for Machine Translation
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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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An open-source toolkit for integrating shallow-transfer rules into phrase-based statistical machine translation
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Choosing the correct paradigm for unknown words in rule-based machine translation systems
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The Universitat d’Alacant hybrid machine translation system for WMT 2011
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Integrating shallow-transfer rules into phrase-based statistical machine translation
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Enriching a statistical machine translation system trained on small parallel corpora with rule-based bilingual phrases
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Abstract:
In this paper, we present a new hybridization approach consisting of enriching the phrase table of a phrase-based statistical machine translation system with bilingual phrase pairs matching structural transfer rules and dictionary entries from a shallow-transfer rule-based machine translation system. We have tested this approach on different small parallel corpora scenarios, where pure statistical machine translation systems suffer from data sparseness. The results obtained show an improvement in translation quality, specially when translating out-of-domain texts that are well covered by the shallow-transfer rule-based machine translation system we have used. ; 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).
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Keyword:
Bilingual phrases; Enriching; Lenguajes y Sistemas Informáticos; Rule-based; Small parallel corpora; Statistical machine translation system
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URL: http://hdl.handle.net/10045/27577
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A Widely Used Machine Translation Service and its Migration to a Free/Open-Source Solution : the Case of Softcatalà
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ScaleMT: a free/open-source framework for building scalable machine translation web services
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