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The toolkit was designed to let translators organize their work and use shared translations, glossaries and translation memories, and was compatible with Microsoft Word, HTML, and other formats. Google Translator Toolkit by default used Google Translate to automatically pre-translate uploaded documents which translators could then improve.
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.
The same text may also not be classified as English. Regardless of the physical keyboard's layout, it is possible to install Unicode-based Hindi keyboard layouts on most modern operating systems. There are many online services available that transliterate text written in Roman to Devanagari accurately, using Hindi dictionaries for reference ...
English, the primary medium of higher education in India, remains inaccessible to even the literate majority of the country.Therefore, there is an urgent need to translate material in all fields like literary, technical, scientific and business etc. so that such material is accessible to a wide range of different language speaking population across the country.
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]
Reverso has been active since 1998, with the aim of providing online translation and linguistic tools to corporate and mass markets. [3] [4] In 2013 it released Reverso Context, a bilingual dictionary tool based on big data and machine learning algorithms. [5] In 2016 Reverso acquired Fleex, a service for learning English via subtitled movies.
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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.
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