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Literal translation, direct translation, or word-for-word translation is the translation of a text done by translating each word separately without analysing how the words are used together in a phrase or sentence. [1] In translation theory, another term for literal translation is metaphrase (as opposed to paraphrase for an analogous translation).
These two types are sometimes referred to as consecutive self-translation and simultaneous self-translation. [6] —Self-translation may even involve more than one target language, whether native or acquired. This is the case with authors like Fausto Cercignani, [7] Alejandro Saravia, [8] and Luigi Donato Ventura. [9]
Google Translate is a multilingual neural machine translation service developed by Google to translate text, documents and websites from one language into another. It offers a website interface, a mobile app for Android and iOS, as well as an API that helps developers build browser extensions and software applications. [3]
From Wikipedia, the free encyclopedia. Redirect page
Gîte du Volcan in Réunion. A gîte or gite (French pronunciation:) is, typically, a holiday rental home in France, but there are many interpretations of the term 'gîte'.'. They range from a gîtes d'etape — a hostel, for walkers and cyclists — to a gîte rural, a holiday home in the country available for rent, often an accessory dwelling
Translation is the communication of the meaning of a source-language text by means of an equivalent target-language text. [1] The English language draws a terminological distinction (which does not exist in every language) between translating (a written text) and interpreting (oral or signed communication between users of different languages ...
If the English article already exists (but a translation would be useful because the article in the other language is of higher quality, or includes additional information): simply place a translation template from the category Category:Expand by language Wikipedia templates on the English article page.
Generative language models are not trained on the translation task, let alone on a parallel dataset. Instead, they are trained on a language modeling objective, such as predicting the next word in a sequence drawn from a large dataset of text. This dataset can contain documents in many languages, but is in practice dominated by English text. [36]