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2. Google Translate - Wikipedia

   en.wikipedia.org/wiki/Google_Translate

   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]

3. Reverso (language tools) - Wikipedia

   en.wikipedia.org/wiki/Reverso_(language_tools)

   Reverso's suite of online linguistic services has over 96 million users, and comprises various types of language web apps and tools for translation and language learning. [11] Its tools support many languages, including Arabic, Chinese, English, French, Hebrew, Spanish, Italian, Turkish, Ukrainian and Russian.

4. DeepL Translator - Wikipedia

   en.wikipedia.org/wiki/DeepL_Translator

   DeepL for Windows translating from Polish to French. The translator can be used for free with a limit of 1,500 characters per translation. Microsoft Word and PowerPoint files in Office Open XML file formats (.docx and .pptx) and PDF files up to 5MB in size can also be translated.

5. Microsoft Translator - Wikipedia

   en.wikipedia.org/wiki/Microsoft_Translator

   Microsoft Translator or Bing Translator is a multilingual machine translation cloud service provided by Microsoft.Microsoft Translator is a part of Microsoft Cognitive Services [1] and integrated across multiple consumer, developer, and enterprise products, including Bing, Microsoft Office, SharePoint, Microsoft Edge, Microsoft Lync, Yammer, Skype Translator, Visual Studio, and Microsoft ...

6. Yandex Translate - Wikipedia

   en.wikipedia.org/wiki/Yandex_Translate

   The system constructs the dictionary of single-word translations based on the analysis of millions of translated texts. In order to translate the text, the computer first compares it to a database of words. The computer then compares the text to the base language models, trying to determine the meaning of an expression in the context of the text.

7. Neural machine translation - Wikipedia

   en.wikipedia.org/wiki/Neural_machine_translation

   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]

8. Literal translation - Wikipedia

   en.wikipedia.org/wiki/Literal_translation

   Literal translation, direct translation, or word-for-word translation is the translation of a text done by translating each word separately without analysing how the words are used together in a phrase or sentence. [1] In translation theory, another term for literal translation is metaphrase (as opposed to paraphrase for an analogous translation).

9. Machine translation - Wikipedia

   en.wikipedia.org/wiki/Machine_translation

   Word-sense disambiguation concerns finding a suitable translation when a word can have more than one meaning. The problem was first raised in the 1950s by Yehoshua Bar-Hillel. [33] He pointed out that without a "universal encyclopedia", a machine would never be able to distinguish between the two meanings of a word. [34]