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Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style Transfer ...
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Unsupervised Translation of German--Lower Sorbian: Exploring Training and Novel Transfer Methods on a Low-Resource Language ...
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Generic resources are what you need: Style transfer tasks without task-specific parallel training data ...
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A set of recommendations for assessing human-machine parity in language translation
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In: Läubli, Samuel orcid:0000-0001-5362-4106 , Castilho, Sheila orcid:0000-0002-8416-6555 , Neubig, Graham, Sennrich, Rico orcid:0000-0002-1438-4741 , Shen, Qinlan and Toral, Antonio orcid:0000-0003-2357-2960 (2020) A set of recommendations for assessing human-machine parity in language translation. Journal of Artificial Intelligence Research, 67 . pp. 653-672. ISSN 1076-9757 (2020)
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Character-level Representations Improve DRS-based Semantic Parsing Even in the Age of BERT ...
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A Set of Recommendations for Assessing Human-Machine Parity in Language Translation ...
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Post-editing effort of a novel with statistical and neural machine translation
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In: Toral, Antonio, Wieling, Martijn and Way, Andy orcid:0000-0001-5736-5930 (2018) Post-editing effort of a novel with statistical and neural machine translation. Frontiers in Digital Humanities, 5 (9). pp. 1-11. ISSN 2297-2668 (2018)
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What level of quality can neural machine translation attain on literary text?
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In: Toral, Antonio orcid:0000-0003-2357-2960 and Way, Andy orcid:0000-0001-5736-5930 (2018) What level of quality can neural machine translation attain on literary text? In: Moorkens, Joss orcid:0000-0003-4864-5986 , Castilho, Sheila orcid:0000-0002-8416-6555 , Gaspari, Federico orcid:0000-0003-3808-8418 and Doherty, S, (eds.) Translation Quality Assessment: From Principles to Practice. Machine Translation: Technologies and Applications book series (MATRA), 1 . Springer, Berlin/Heidelberg, 263 -287. ISBN 978-3-319-91240-0 (2018)
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Post-editing effort of a novel with statistical and neural machine translation
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In: Toral, Antonio orcid:0000-0003-2357-2960 , Wieling, Martijn orcid:0000-0003-0434-1526 and Way, Andy orcid:0000-0001-5736-5930 (2018) Post-editing effort of a novel with statistical and neural machine translation. Frontiers in Digital Humanities, 5 . ISSN 2297-2668 (2018)
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Attaining the unattainable? Reassessing claims of human parity in neural machine translation
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In: Toral, Antonio orcid:0000-0003-2357-2960 , Castilho, Sheila orcid:0000-0002-8416-6555 , Hu, Ke and Way, Andy orcid:0000-0001-5736-5930 (2018) Attaining the unattainable? Reassessing claims of human parity in neural machine translation. In: Third Conference on Machine Translation (WMT), 31 Oct- 1 Nov 2018, Brussels, Belgium. ISBN 978-1-948087-81-0 (2018)
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Quantitative Fine-Grained Human Evaluation of Machine Translation Systems: a Case Study on English to Croatian ...
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Quantitative Fine-grained Human Evaluation of Machine Translation Systems: a Case Study on English to Croatian
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In: Articles (2018)
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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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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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CloudLM: a cloud-based language model for machine translation
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In: Ferrández-Tordera, Jorge, Ortiz-Rojas, Sergio and Toral, Antonio orcid:0000-0003-2357-2960 (2016) CloudLM: a cloud-based language model for machine translation. Prague Bulletin of Mathematical Linguistics (105). pp. 51-61. ISSN 1804-0462 (2016)
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Abstract:
Language models (LMs) are an essential element in statistical approaches to natural language processing for tasks such as speech recognition and machine translation (MT). The advent of big data leads to the availability of massive amounts of data to build LMs, and in fact, for the most prominent languages, using current techniques and hardware, it is not feasible to train LMs with all the data available nowadays. At the same time, it has been shown that the more data is used for a LM the better the performance, e.g. for MT, without any indication yet of reaching a plateau. This paper presents CloudLM, an open-source cloud-based LM intended for MT, which allows to query distributed LMs. CloudLM relies on Apache Solr and provides the functionality of state-of-the-art language modelling (it builds upon KenLM), while allowing to query massive LMs (as the use of local memory is drastically reduced), at the expense of slower decoding speed.
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Keyword:
Machine translating
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URL: http://doras.dcu.ie/23306/
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