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Anusaaraka is an English to Hindi language accessing (translation) software, which employs algorithms derived from Pāṇini's Ashtadhyayi (Grammar rules). [1] [2] The software is being developed by the Chinmaya International Foundation (CIF) [3] at the International Institute of Information Technology, Hyderabad (IIIT-H) and the University of Hyderabad Department of Sanskrit Studies. [4]
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]
The company was established in La Jolla in California to work on translation of Russian to English text for the United States Air Force during the Cold War. [5] Large numbers of Russian scientific and technical documents were translated using SYSTRAN under the auspices of the USAF Foreign Technology Division (later the National Air and Space ...
The company executes text, digital, audio, and video translations. Unlike other translation platforms and software, LILT uses a "human-in-the-loop" system, where a human translator can modify a word when he/she encounters it. [2] [5] [6] [7] It helped for translation and early warning during Hurricane Fiona and Hurricane Ian.
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.
The software engineer is supposed to spend his days typically writing code for Google’s tools and products. It sounds like laborious work, but he says he only works one hour per day.
By 2020, the system had been replaced by another deep learning system based on a Transformer encoder and an RNN decoder. [10] GNMT improved on the quality of translation by applying an example-based (EBMT) machine translation method in which the system learns from millions of examples of language translation. [2]
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