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Azhagi is the first successful Tamil transliteration tool [6] which has many users throughout the world. Azhagi helps the user to create and edit contents in several Indian languages including Tamil, Hindi, Sanskrit, Telugu, Kannada, Malayalam, Marathi, Konkani, Gujarati, Bengali, Punjabi, Oriya and Assamese without having to know how to type in these languages.
Dravidian languages include Tamil, Malayalam, Kannada, Telugu, and a number of other languages spoken mainly in South Asia. The list is by no means exhaustive. Some of the words can be traced to specific languages, but others have disputed or uncertain origins. Words of disputed or less certain origin are in the "Dravidian languages" list.
Google's service for Indic languages was previously available as an online text editor, named Google Indic Transliteration. Other language transliteration capabilities were added (beyond just Indic languages) and it was renamed simply Google transliteration.
To create awareness among computer users in the use of free software. To work towards usage of free software in all stream of sciences and research. To take forward implementation and usage of free software in school education, academics and higher education. To work towards e-literacy and bridging digital divide based on free software and ...
Tamil Lexicon (Tamil: தமிழ்ப் பேரகராதி Tamiḻ Pērakarāti) is a twelve-volume dictionary of the Tamil language. Published by the University of Madras , it is said to be the most comprehensive dictionary of the Tamil language to date.
Google Translate previously first translated the source language into English and then translated the English into the target language rather than translating directly from one language to another. [11] A July 2019 study in Annals of Internal Medicine found that "Google Translate is a viable, accurate tool for translating non–English-language ...
Computer software can encounter differences above and beyond straightforward translation of words and phrases, because computer programs can generate content dynamically. These differences may need to be taken into account by the internationalization process in preparation for translation.
Previously, machine translation was based on "the meaning of the text" model: take any language, translate the words in the universal language of the senses, and then translate these meanings in the words of another language – and obtain the translated text. This model prevailed in the 1970s-1980s and automated in the 1990s.