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  2. Almaany - Wikipedia

    en.wikipedia.org/wiki/Almaany

    It has Arabic to English translations and English to Arabic, as well as a significant quantity of technical terminology. It is useful to translators as its search results are given in context. [ 6 ] Almaany offers correspondent meanings for Arabic terms with semantically similar words and is widely used in Arabic language research. [ 7 ]

  3. English-Arabic Parallel Corpus of United Nations Texts

    en.wikipedia.org/wiki/English-Arabic_Parallel...

    It consists of two subcorpora; one contains the English originals and the other their Arabic translations. As for the English subcorpus, it contains 3,794,677 word tokens, with 78,606 word types. The Arabic subcorpus has a slightly fewer word tokens (3,755,741), yet differs greatly in terms of the number of word types, which is 143,727.

  4. Google Neural Machine Translation - Wikipedia

    en.wikipedia.org/wiki/Google_Neural_Machine...

    For example, it might be trained just for Japanese-English and Korean-English translation, but can perform Japanese-Korean translation. The system appears to have learned to produce a language-independent intermediate representation of language (an "interlingua"), which allows it to perform zero-shot translation by converting from and to the ...

  5. Rule-based machine translation - Wikipedia

    en.wikipedia.org/wiki/Rule-based_machine_translation

    Rule-based machine translation (RBMT; "Classical Approach" of MT) is machine translation systems based on linguistic information about source and target languages basically retrieved from (unilingual, bilingual or multilingual) dictionaries and grammars covering the main semantic, morphological, and syntactic regularities of each language respectively.

  6. 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]

  7. Reverso (language tools) - Wikipedia

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

    Reverso has been active since 1998, with the aim of providing online translation and linguistic tools to corporate and mass markets. [3] [4] In 2013 it released Reverso Context, a bilingual dictionary tool based on big data and machine learning algorithms. [5] In 2016 Reverso acquired Fleex, a service for learning English via subtitled movies.

  8. 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]

  9. Arabic machine translation - Wikipedia

    en.wikipedia.org/wiki/Arabic_machine_translation

    Arabic is one of the major languages that have been given attention by machine translation (MT) researchers since the very early days of MT and specifically in the U.S. The language has always been considered "due to its morphological, syntactic, phonetic and phonological properties [to be] one of the most difficult languages for written and spoken language processing."