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Google Translate is a web-based free-to-user translation service developed by Google in April 2006. [11] It translates multiple forms of texts and media such as words, phrases and webpages. Originally, Google Translate was released as a statistical machine translation service. [11] The input text had to be translated into English first before ...
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. A July 2019 study in Annals of Internal Medicine found that "Google Translate is a viable, accurate tool for translating non–English-language ...
1.1.0. Yes. 300+. Competitive performance for Chinese translation tasks; statistical machine translation. Supports phrase-based, hierarchical phrase-based, and syntax-based (string-to-tree, tree-to-string, and tree-to-tree) models for research purposes. OpenLogos. Windows, Linux. GPL or paid initiative taker. No fee required.
The accuracy of Google Translate continues to improve, and in many cases approaches the accuracy of human translation. Use of non-English sources can help counter systemic bias on Wikipedia, which skews to Anglocentric and Eurocentric perspectives. Cons. Accuracy may not be sufficient for all uses, and human translation is still more accurate.
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Google (GOOG, GOOGL) took the wraps off of a new prototype pair of augmented reality glasses that can automatically translate speech for wearers that speak different languages.Unveiled during the ...
A number of computer-assisted translation software and websites exists for various platforms and access types. According to a 2006 survey undertaken by Imperial College of 874 translation professionals from 54 countries, primary tool usage was reported as follows: Trados (35%), Wordfast (17%), Déjà Vu (16%), SDL Trados 2006 (15%), SDLX (4%), STAR Transit [fr; sv] (3%), OmegaT (3%), others (7%).
Machine translation is use of either rule-based or probabilistic (i.e. statistical and, most recently, neural network-based) machine learning approaches to translation of text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages.
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