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T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.
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]
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 ...
The authors found that English remained at 45 percent of content for 2005 to the end of the study but believe this was due to the bias of search engines indexing more English-language content rather than a true stabilization of the percentage of content in English on the World Wide Web. [2] The number of non-English web pages is rapidly expanding.
Rule-based, deep parser based, paninian framework based; all programs and language data are free and open-source Apertium: Cross-platform (web application), Unix compatible, precompiled packages available for Debian: GPL: No fee required: 3.4.2: Yes: Rule-based, shallow transfer; all programs and language data are free and open source Babylon ...
Lexical transfer. This is basically dictionary translation; the source language lemma (perhaps with sense information) is looked up in a bilingual dictionary and the translation is chosen. Structural transfer. While the previous stages deal with words, this stage deals with larger constituents, for example phrases and chunks. Typical features ...
Demonstration of the languages which are used in the process of translating using a bridge language. Interlingual machine translation is one of the classic approaches to machine translation. In this approach, the source language, i.e. the text to be translated is transformed into an interlingua, i.e., an abstract language-independent ...
The Toolkit began in June 2009 with only one source language—English—and forty-seven target languages, but later support 345 source languages and 345 target languages for approximately 100,000 language pairs. [6] Google Translator Toolkit's user interface was available in eighty-five languages: [7]