Machine translation of English content: A comparative study of different methods

Based on neural machine translation, this article introduced the ConvS2S system and transformer system, designed a semantic sharing combined transformer system to improve translation quality, and compared the three systems on the NIST dataset. The results showed that the operation speed of the seman...

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Autor principal:	Xue Jinfeng
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	english machine translation transformer system semantic sharing convs2s system Science Q Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/d4729486a0154ba6aa94f712c3cf65bd
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id	oai:doaj.org-article:d4729486a0154ba6aa94f712c3cf65bd
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spelling	oai:doaj.org-article:d4729486a0154ba6aa94f712c3cf65bd2021-12-05T14:10:51ZMachine translation of English content: A comparative study of different methods2191-026X10.1515/jisys-2021-0150https://doaj.org/article/d4729486a0154ba6aa94f712c3cf65bd2021-09-01T00:00:00Zhttps://doi.org/10.1515/jisys-2021-0150https://doaj.org/toc/2191-026XBased on neural machine translation, this article introduced the ConvS2S system and transformer system, designed a semantic sharing combined transformer system to improve translation quality, and compared the three systems on the NIST dataset. The results showed that the operation speed of the semantic sharing combined transformer system was the highest, reaching 3934.27 words per second; the BLEU value of the ConvS2S system was the smallest, followed by the transformer system and the semantic sharing combined transformer system. Taking NIST08 as an example, the BLEU values of the designed system were 4.74 and 1.49 higher than the other two systems. The analysis of examples showed that the semantic sharing combined transformer had higher translation quality. The experimental results show that the proposed system is reliable in English content translation and can be further promoted and applied in practice.Xue JinfengDe Gruyterarticleenglishmachine translationtransformer systemsemantic sharingconvs2s systemScienceQElectronic computers. Computer scienceQA75.5-76.95ENJournal of Intelligent Systems, Vol 30, Iss 1, Pp 980-987 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	english machine translation transformer system semantic sharing convs2s system Science Q Electronic computers. Computer science QA75.5-76.95
spellingShingle	english machine translation transformer system semantic sharing convs2s system Science Q Electronic computers. Computer science QA75.5-76.95 Xue Jinfeng Machine translation of English content: A comparative study of different methods
description	Based on neural machine translation, this article introduced the ConvS2S system and transformer system, designed a semantic sharing combined transformer system to improve translation quality, and compared the three systems on the NIST dataset. The results showed that the operation speed of the semantic sharing combined transformer system was the highest, reaching 3934.27 words per second; the BLEU value of the ConvS2S system was the smallest, followed by the transformer system and the semantic sharing combined transformer system. Taking NIST08 as an example, the BLEU values of the designed system were 4.74 and 1.49 higher than the other two systems. The analysis of examples showed that the semantic sharing combined transformer had higher translation quality. The experimental results show that the proposed system is reliable in English content translation and can be further promoted and applied in practice.
format	article
author	Xue Jinfeng
author_facet	Xue Jinfeng
author_sort	Xue Jinfeng
title	Machine translation of English content: A comparative study of different methods
title_short	Machine translation of English content: A comparative study of different methods
title_full	Machine translation of English content: A comparative study of different methods
title_fullStr	Machine translation of English content: A comparative study of different methods
title_full_unstemmed	Machine translation of English content: A comparative study of different methods
title_sort	machine translation of english content: a comparative study of different methods
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/d4729486a0154ba6aa94f712c3cf65bd
work_keys_str_mv	AT xuejinfeng machinetranslationofenglishcontentacomparativestudyofdifferentmethods
_version_	1718371691280728064

Machine translation of English content: A comparative study of different methods

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