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Multimedia translation, also sometimes referred to as Audiovisual translation, is a specialized branch of translation which deals with the transfer of multimodal and multimedial texts into another language and/or culture. [1] and which implies the use of a multimedia electronic system in the translation or in the transmission process.
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 ]
Transcreation is a term coined from the words "translation" and "creation", and a concept used in the field of translation studies to describe the process of adapting a message from one language to another, while maintaining its intent, style, tone, and context.
DeepL Translator is a neural machine translation service that was launched in August 2017 and is owned by Cologne-based DeepL SE. The translating system was first developed within Linguee and launched as entity DeepL .
Google Dictionary is an online dictionary service of Google that can be accessed with the "define" operator and other similar phrases [note 1] in Google Search. [2] It is also available in Google Translate and as a Google Chrome extension. The dictionary content is licensed from Oxford University Press's Oxford Languages. [3]
Untranslatability is the property of text or speech for which no equivalent can be found when translated into another (given) language. A text that is considered to be untranslatable is considered a lacuna, or lexical gap. The term arises when describing the difficulty of achieving the so-called perfect translation.
Tamil Lexicon (Tamil: தமிழ்ப் பேரகராதி Tamiḻ Pērakarāti) is a twelve-volume dictionary of the Tamil language. Published by the University of Madras , it is said to be the most comprehensive dictionary of the Tamil language to date.
Google Translate's NMT system uses a large artificial neural network capable of deep learning. [1] [2] [3] By using millions of examples, GNMT improves the quality of translation, [2] using broader context to deduce the most relevant translation.