A Study on the Intelligent Translation Model for English Incorporating Neural Network Migration Learning

Under the current artificial intelligence boom, machine translation is a research direction of natural language processing, which has important scientific research value and practical value. In practical applications, the variability of language, the limited capability of representing semantic infor...

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Autor principal:	Yanbo Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Technology T Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/a75b161a1ba14300af6af65b29af53b8
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id	oai:doaj.org-article:a75b161a1ba14300af6af65b29af53b8
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spelling	oai:doaj.org-article:a75b161a1ba14300af6af65b29af53b82021-11-29T00:56:16ZA Study on the Intelligent Translation Model for English Incorporating Neural Network Migration Learning1530-867710.1155/2021/1244389https://doaj.org/article/a75b161a1ba14300af6af65b29af53b82021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/1244389https://doaj.org/toc/1530-8677Under the current artificial intelligence boom, machine translation is a research direction of natural language processing, which has important scientific research value and practical value. In practical applications, the variability of language, the limited capability of representing semantic information, and the scarcity of parallel corpus resources all constrain machine translation towards practicality and popularization. In this paper, we conduct deep mining of source language text data to express complex, high-level, and abstract semantic information using an appropriate text data representation model; then, for machine translation tasks with a large amount of parallel corpus, I use the capability of annotated datasets to build a more effective migration learning-based end-to-end neural network machine translation model on a supervised algorithm; then, for machine translation tasks with parallel corpus data resource-poor language machine translation tasks, migration learning techniques are used to prevent the overfitting problem of neural networks during training and to improve the generalization ability of end-to-end neural network machine translation models under low-resource conditions. Finally, for language translation tasks where the parallel corpus is extremely scarce but monolingual corpus is sufficient, the research focuses on unsupervised machine translation techniques, which will be a future research trend.Yanbo ZhangHindawi-WileyarticleTechnologyTTelecommunicationTK5101-6720ENWireless Communications and Mobile Computing, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology T Telecommunication TK5101-6720
spellingShingle	Technology T Telecommunication TK5101-6720 Yanbo Zhang A Study on the Intelligent Translation Model for English Incorporating Neural Network Migration Learning
description	Under the current artificial intelligence boom, machine translation is a research direction of natural language processing, which has important scientific research value and practical value. In practical applications, the variability of language, the limited capability of representing semantic information, and the scarcity of parallel corpus resources all constrain machine translation towards practicality and popularization. In this paper, we conduct deep mining of source language text data to express complex, high-level, and abstract semantic information using an appropriate text data representation model; then, for machine translation tasks with a large amount of parallel corpus, I use the capability of annotated datasets to build a more effective migration learning-based end-to-end neural network machine translation model on a supervised algorithm; then, for machine translation tasks with parallel corpus data resource-poor language machine translation tasks, migration learning techniques are used to prevent the overfitting problem of neural networks during training and to improve the generalization ability of end-to-end neural network machine translation models under low-resource conditions. Finally, for language translation tasks where the parallel corpus is extremely scarce but monolingual corpus is sufficient, the research focuses on unsupervised machine translation techniques, which will be a future research trend.
format	article
author	Yanbo Zhang
author_facet	Yanbo Zhang
author_sort	Yanbo Zhang
title	A Study on the Intelligent Translation Model for English Incorporating Neural Network Migration Learning
title_short	A Study on the Intelligent Translation Model for English Incorporating Neural Network Migration Learning
title_full	A Study on the Intelligent Translation Model for English Incorporating Neural Network Migration Learning
title_fullStr	A Study on the Intelligent Translation Model for English Incorporating Neural Network Migration Learning
title_full_unstemmed	A Study on the Intelligent Translation Model for English Incorporating Neural Network Migration Learning
title_sort	study on the intelligent translation model for english incorporating neural network migration learning
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/a75b161a1ba14300af6af65b29af53b8
work_keys_str_mv	AT yanbozhang astudyontheintelligenttranslationmodelforenglishincorporatingneuralnetworkmigrationlearning AT yanbozhang studyontheintelligenttranslationmodelforenglishincorporatingneuralnetworkmigrationlearning
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A Study on the Intelligent Translation Model for English Incorporating Neural Network Migration Learning

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