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2. DeepL Translator - Wikipedia

   en.wikipedia.org/wiki/DeepL_Translator

   The reception of DeepL Translator has been generally positive. TechCrunch appreciates it for the accuracy of its translations and stating that it was more accurate and nuanced than Google Translate. [3] Le Monde thank its developers for translating French text into more "French-sounding" expressions. [38]

3. 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 ]

4. Google Neural Machine Translation - Wikipedia

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

   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 ...

5. 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 ]

6. Buckwalter transliteration - Wikipedia

   en.wikipedia.org/wiki/Buckwalter_transliteration

   If the Latin text is not explicitly marked, it is a challenge to distinguish transliterated Arabic from Latin. If transliterated text with embedded Latin is later transliterated back to Arabic, the Latin text will be transliterated into garbage Arabic. Finally, another important decision to make is how much normalization of the Arabic text ...

7. English-Arabic Parallel Corpus of United Nations Texts

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

   The EAPCOUNT comprises 341 texts aligned on a paragraph basis, which means texts in English along with their translational counterparts in Arabic. 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 ...