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TermEval: an automatic metric for evaluating terminology translation in MT
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In: Haque, Rejwanul orcid:0000-0003-1680-0099 , Hasanuzzaman, Mohammed orcid:0000-0003-1838-0091 and Way, Andy orcid:0000-0001-5736-5930 (2019) TermEval: an automatic metric for evaluating terminology translation in MT. In: CICLing 2019, the 20th International Conference on Computational Linguistics and Intelligent Text Processing, 07-13 Apr 2019, La Rochelle, France. (2019)
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TermEval: an automatic metric for evaluating terminology translation in MT
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In: Haque, Rejwanul orcid:0000-0003-1680-0099 , Hasanuzzaman, Mohammed orcid:0000-0003-1838-0091 and Way, Andy orcid:0000-0001-5736-5930 (2019) TermEval: an automatic metric for evaluating terminology translation in MT. In: CICLing 2019: the 20th International Conference on Computational Linguistics and Intelligent Text Processing, 7-13 Apr 2019, La Rochelle, France. (2019)
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Improved Arabic–Chinese Machine Translation with Linguistic Input Features
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In: Future Internet ; Volume 11 ; Issue 1 (2019)
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Terminology Translation in Low-Resource Scenarios
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In: Information ; Volume 10 ; Issue 9 (2019)
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Fast machine translation on parallel and massively parallel hardware
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Advanced techniques for domain adaptation in Statistical Machine Translation
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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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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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| 10 |
Is statistical machine translation approach dead?
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In: ICNLSSP 2017 - International Conference on Natural Language, Signal and Speech Processing ; https://hal.inria.fr/hal-01660016 ; ICNLSSP 2017 - International Conference on Natural Language, Signal and Speech Processing, ISGA, Dec 2017, Casablanca, Morocco. pp.1-5 ; http://icnlssp.isga.ma (2017)
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| 11 |
Phrase-Based Language Model in Statistical Machine Translation
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In: ISSN: 0976-0962 ; International Journal of Computational Linguistics and Applications ; https://hal.inria.fr/hal-01336485 ; International Journal of Computational Linguistics and Applications, Alexander Gelbukh, 2016 (2016)
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Genuine phrase-based statistical machine translation with supervision
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| 13 |
Integrating Rules and Dictionaries from Shallow-Transfer Machine Translation into Phrase-Based Statistical 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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Morphology-Aware Alignments for Translation to and from a Synthetic Language
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In: International Workshop on Spoken Language Translation ; https://hal.archives-ouvertes.fr/hal-01635005 ; International Workshop on Spoken Language Translation, Jan 2015, Da Nang, Vietnam (2015)
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| 16 |
Phrase extraction and rescoring in statistical machine translation
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Srivastava, Ankit Kumar. - : Dublin City University. Centre for Next Generation Localisation (CNGL), 2014. : Dublin City University. School of Computing, 2014
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In: Srivastava, Ankit Kumar (2014) Phrase extraction and rescoring in statistical machine translation. PhD thesis, Dublin City University. (2014)
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Translating sentences from ‘original’ to ‘simplified’ Spanish ; Traducción de frases del español ‘original’ al español ‘simplificado’
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Štajner, Sanja. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2014
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CCG-augmented hierarchical phrase-based statistical machine translation
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In: Almaghout, Hala (2013) CCG-augmented hierarchical phrase-based statistical machine translation. PhD thesis, Dublin City University. (2013)
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Abstract:
Augmenting Statistical Machine Translation (SMT) systems with syntactic information aims at improving translation quality. Hierarchical Phrase-Based (HPB) SMT takes a step toward incorporating syntax in Phrase-Based (PB) SMT by modelling one aspect of language syntax, namely the hierarchical structure of phrases. Syntax Augmented Machine Translation (SAMT) further incorporates syntactic information extracted using context free phrase structure grammar (CF-PSG) in the HPB SMT model. One of the main challenges facing CF-PSG-based augmentation approaches for SMT systems emerges from the difference in the definition of the constituent in CF-PSG and the ‘phrase’ in SMT systems, which hinders the ability of CF-PSG to express the syntactic function of many SMT phrases. Although the SAMT approach to solving this problem using ‘CCG-like’ operators to combine constituent labels improves syntactic constraint coverage, it significantly increases their sparsity, which restricts translation and negatively affects its quality. In this thesis, we address the problems of sparsity and limited coverage of syntactic constraints facing the CF-PSG-based syntax augmentation approaches for HPB SMT using Combinatory Cateogiral Grammar (CCG). We demonstrate that CCG’s flexible structures and rich syntactic descriptors help to extract richer, more expressive and less sparse syntactic constraints with better coverage than CF-PSG, which enables our CCG-augmented HPB system to outperform the SAMT system. We also try to soften the syntactic constraints imposed by CCG category nonterminal labels by extracting less fine-grained CCG-based labels. We demonstrate that CCG label simplification helps to significantly improve the performance of our CCG category HPB system. Finally, we identify the factors which limit the coverage of the syntactic constraints in our CCG-augmented HPB model. We then try to tackle these factors by extending the definition of the nonterminal label to be composed of a sequence of CCG categories and augmenting the glue grammar with CCG combinatory rules. We demonstrate that our extension approaches help to significantly increase the scope of the syntactic constraints applied in our CCG-augmented HPB model and achieve significant improvements over the HPB SMT baseline.
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Keyword:
Hierarchical Phrase-Based SMT; Machine learning; Machine translating; Statistical Machine Translation
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URL: http://doras.dcu.ie/17450/
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| 19 |
Generalizing sampling-based multilingual alignment
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In: ISSN: 0922-6567 ; EISSN: 1573-0573 ; Machine Translation ; https://hal.archives-ouvertes.fr/hal-00753859 ; Machine Translation, Springer Verlag, 2013, 27 (1), pp.1-23. ⟨10.1007/s10590-012-9126-0⟩ (2013)
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Improved Phrase Translation Modeling Using Maximum A-Posteriori (MAP) Adaptation
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In: DTIC (2013)
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