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Word Lens was an augmented reality translation application from Quest Visual. [1] Word Lens used the built-in cameras on smartphones and similar devices to quickly scan and identify foreign text (such as that found in a sign or a menu), and then translated and displayed the words in another language on the device's display.
One of the key reasons why Rosetta 2 provides such a high level of translation efficiency is the support of x86-64 memory ordering in the Apple M1 SOC. [14] The SOC also has dedicated instructions for computing x86 flags. [15] Although Rosetta 2 works for most software, some software does not work at all [16] or is reported to be "sluggish ...
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 ...
By providing translators with the most advanced translation software free of charge, they aimed to foster a mutually beneficial relationship between translators and machine translation, where translators would teach machines to translate better, and machines would improve in real time to provide better translation suggestions.
Otter.ai, Inc. is an American transcription software company based in Mountain View, California. The company develops speech to text transcription applications using artificial intelligence and machine learning. Its software, called Otter, shows captions for live speakers, and generates written transcriptions of speech. [1]
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MateCat ("Machine Translation Enhanced Computer Assisted Translation") is a 3-year research project (Nov 2011 – Oct 2014) funded by the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement No. 287688. [1] It has received over €2,500,000 of European funds. [2]
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