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DeepL Translator is a neural machine translation service that was launched in August 2017 and is owned by Cologne-based DeepL SE. The translating system was first developed within Linguee and launched as entity DeepL .
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 ]
Arabic, Catalan, Danish, Dutch, Finnish, French, German, Italian, Norwegian, Polish, Portuguese, Spanish, Swedish, Turkish. If the non-English citation template is supported by a translator (see list), all you need to do is copy the citation from the source and paste it into the en-wiki article, preview, fix any errors, and publish.
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 ...
Reverso is a French company specialized in AI-based language tools, translation aids, and language services. [2] These include online translation based on neural machine translation (NMT), contextual dictionaries, online bilingual concordances, grammar and spell checking and conjugation tools.
Wikipedia is a multilingual project; as such, we may have articles on one subject available in many languages.The various languages each appear in semi-separate wikis, linked by interlanguage links.
A certified translation consists of the source-language text, the target-language text, and a statement signed by the translator or translation company representative that the translator or translation company representative believes the target-language text to be an accurate and complete translation of the source-language text.
Generative language models are not trained on the translation task, let alone on a parallel dataset. Instead, they are trained on a language modeling objective, such as predicting the next word in a sequence drawn from a large dataset of text. This dataset can contain documents in many languages, but is in practice dominated by English text. [36]
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