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dc.contributor.authorADDA, Sara-
dc.contributor.authorAZOUZE, Imane-
dc.contributor.authorCHAABANE, Fadihla-
dc.date.accessioned2023-01-24T08:36:39Z-
dc.date.available2023-01-24T08:36:39Z-
dc.date.issued2022-
dc.identifier.urihttp://dspace.univ-tiaret.dz:80/handle/123456789/7931-
dc.description.abstractThe present study attempts to investigate and analyse the contextual machine of translation. Moreover, the discipline of translation grew in tandem with global and linguistic contacts. At the same time, machine translation technology evolved. Indeed, this study examines to which extent on the significant changes that came about by improvements in computer technology machine translation improved as well with the collaboration between linguists and computer scientists. This research is aimed at the history and evolution of Machine Translation, it begins with a background description of translation, machine translation, and how the latter works by investigating the two most well-known machine translation systems in use today Google Translate and Reverso Context. In order to confirm the research hypothesis and answer the research questions we adopted descriptive-analytical approach. Therefore, to conduct this research we have compared the outcome translations of both Google Translate and Reverso Context and as well as highlighting the drawbacks and benefits of using any of them.The obtained results seem to be highly significant since it shows that the ultimate goal of this research is to overcome the variations between machine translations and its manipulation on the meaning and to determine the misinterpretation that might machine translation cause. As a result, this research shows that the new phase in which grammar-based approaches are replaced by "statistical approaches." results a translation that provides a solid understanding of the original meaning, but are far from the best translation a human can produce; In other words, despite the great hopes and efforts put into machine translation as they attempted to solve some of the fundamental difficulties in MTL, human translation tends to be more accurate.en_US
dc.language.isoenen_US
dc.publisherUniversité Ibn Khaldoun -Tiaret-en_US
dc.subjectTranslation , Context , Machine translation, Human translation , Google translation, Reverso context translation.en_US
dc.titleEvaluation of Contextual Machine Translation.en_US
dc.title.alternativeCase Study of Google Translate and Reverso Context Translateen_US
dc.typeThesisen_US
Collection(s) :Master

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