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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.
photo text translation feature (uses its own OCR (optical character recognition) technology) – in apps for mobile phones; [12] the "Suggest translation" button (user patches to help improve the quality of machine translations); the "Favorites" section, where you can add translations of individual words and sentences; virtual keyboard.
Image translation is the machine translation of images of printed text (posters, banners, menus, screenshots etc.). This is done by applying optical character recognition (OCR) technology to an image to extract any text contained in the image, and then have this text translated into a language of their choice, and the applying digital image processing on the original image to get the ...
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 .
Machine translation is use of computational techniques to translate text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages. Early approaches were mostly rule-based or statistical. These methods have since been superseded by neural machine translation [1] and large language models ...
Suppose the writer wishes to use some English text (a left-to-right script) into a paragraph written in Arabic or Hebrew (a right-to-left script) with non-alphabetic characters to the right of the English text. For example, the writer wants to translate, "The language C++ is a programming language used..." into Arabic.
Kashida or Kasheeda (Persian: کَشِیدَه; kašīda; [note 1] lit. "extended", "stretched", "lengthened"), also known as Tatweel or Tatwīl (Arabic: تَطْوِيل, taṭwīl), is a type of justification in the Arabic language and in some descendant cursive scripts. [1]
Arabic is one of the major languages that have been given attention by machine translation (MT) researchers since the very early days of MT and specifically in the U.S. The language has always been considered "due to its morphological, syntactic, phonetic and phonological properties [to be] one of the most difficult languages for written and spoken language processing."