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Among the top 100 words in the English language, which make up more than 50% of all written English, the average word has more than 15 senses, [134] which makes the odds against a correct translation about 15 to 1 if each sense maps to a different word in the target language. Most common English words have at least two senses, which produces 50 ...
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 ...
A DMT system is designed for a specific source and target language pair and the translation unit of which is usually a word. Translation is then performed on representations of the source sentence structure and meaning respectively through syntactic and semantic transfer approaches. A transfer-based machine translation system involves three ...
GNMT's proposed architecture of system learning was first tested on over a hundred languages supported by Google Translate. [2] With the large end-to-end framework, the system learns over time to create better, more natural translations. [1] GNMT attempts to translate whole sentences at a time, rather than just piece by piece. [1]
Hyphenate all numbers under 100 that need more than one word. For example, $73 is written as “seventy-three,” and the words for $43.50 are “Forty-three and 50/100.”
Neural machine translation (NMT) is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.
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]
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