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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]
It was bootstrapped by EkStep Foundation in late 2019 as a solution to enable easier translation of legal documents between English and Indic languages. Creating Anuvaad platform allowed legal entities to digitize & translate the Orders/Judgements using an easy to use user interface.
The new translation engine was first enabled for eight languages: to and from English and French, German, Spanish, Portuguese, Chinese, Japanese, Korean and Turkish in November 2016. [24] In March 2017, three additional languages were enabled: Russian, Hindi and Vietnamese along with Thai for which support was added later.
In India, Romanised Hindi is the dominant form of expression online. In an analysis of YouTube comments, Palakodety et al., identified that 52% of comments were in Romanised Hindi, 46% in English, and 1% in Devanagari Hindi. [9] Romanised Hindi is also used by some newspapers such as The Times of India.
DeepL for Windows translating from Polish to French. The translator can be used for free with a limit of 1,500 characters per translation. Microsoft Word and PowerPoint files in Office Open XML file formats (.docx and .pptx) and PDF files up to 5MB in size can also be translated.
The word for the concept of "translation" in English and in some other European languages derives from the Latin noun translatio, [6] which comes from trans, "across" + ferre, "to bring" – with -latio coming from latus, the past participle of ferre). Thus, translatio is the "bringing across" of a text from one language to another. [7]
Bhashini is an Indian government project developed by Ministry of Electronics and Information Technology under its "National Language Translation Mission." It aims to help Indian citizens translate content in various Indian languages and enable effective communication among different-language speakers across India, and thus reduce the language barrier in India.
For example, statistical machine translation (SMT) typically outperforms example-based machine translation (EBMT), but researchers found that when evaluating English to French translation, EBMT performs better. [64] The same concept applies for technical documents, which can be more easily translated by SMT because of their formal language.
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