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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 ...
Video of the process of scanning and real-time optical character recognition (OCR) with a portable scanner. Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene photo (for example the text on signs and ...
Yandex Translate (Russian: Яндекс Переводчик, romanized: Yandeks Perevodchik) is a web service provided by Yandex, intended for the translation of web pages into another language. The service uses a self-learning statistical machine translation , [ 3 ] developed by Yandex. [ 4 ]
The following table compares the number of languages which the following machine translation programs can translate between. (Moses and Moses for Mere Mortals allow you to train translation models for any language pair, though collections of translated texts (parallel corpus) need to be provided by the user.
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 .
For example, Morse code for the Arabic letter ţā' (ط) is • • — (dit-dit-dah). That same Morse code sequence represents the letter U in the Latin alphabet. Hence the SATTS equivalent for ţā' is U. In the Morse-code era, when Arabic language Morse signals were copied down by non-Arab code clerks, the text came out in SATTS.
The first step in scanlation is to obtain the "raws" or the original content in print form, then to scan and send the images to the translator and the cleaner. The translator reads original text from the raws and translates into the desired language of release, then sends the translated text to a proof-reader to check for accuracy.
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."
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