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Project Naptha is a browser extension software for Google Chrome that allows users to highlight, copy, edit and translate text from within images. [1] It was created by developer Kevin Kwok, [2] and released in April 2014 as a Chrome add-on. This software was first made available only on Google Chrome, downloadable from the Chrome Web Store.
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]
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.
Naver Papago (Korean: 네이버 파파고), shortened to Papago and stylized as papago, is a multilingual machine translation cloud service provided by Naver Corporation. The name Papago comes from the Esperanto word for parrot , Esperanto being a constructed language.
While dragging its capture box in any text from any browsers, then a pop-up box appears and Babylon could easily grasp it. Babylon provides full text translation, full Web page and full document translation in many languages and supports integration with Microsoft Office. Babylon enables the translation of Microsoft Word documents and plain ...
Google Input Tools, also known as Google IME, is a set of input method editors by Google for 22 languages, including Amharic, Arabic, Bengali, Chinese, Greek ...
Google Translator Toolkit was [1] an online computer-assisted translation tool (CAT)—a web application designed to permit translators to edit the translations that Google Translate automatically generated using its own and/or user-uploaded files of appropriate glossaries and translation memory.
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.
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