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A rendition of the Vauquois triangle, illustrating the various approaches to the design of machine translation systems.. The direct, transfer-based machine translation and interlingual machine translation methods of machine translation all belong to RBMT but differ in the depth of analysis of the source language and the extent to which they attempt to reach a language-independent ...
Machine translation has also been used for translating Wikipedia articles and could play a larger role in creating, updating, expanding, and generally improving articles in the future, especially as the MT capabilities may improve. There is a "content translation tool" which allows editors to more easily translate articles across several select ...
These articles were translated by professional translators into a series of language pairs, and then translated back into English using the machine translation systems. It was decided that this was not adequate for a standalone method of comparing systems and as such abandoned due to issues with the modification of meaning in the process of ...
Machine translation is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one natural language to another. In the 1950s, machine translation became a reality in research, although references to the subject can be found as early as the 17th century.
Transfer-based machine translation is a type of machine translation (MT). It is currently one of the most widely used methods of machine translation. In contrast to the simpler direct model of MT, transfer MT breaks translation into three steps: analysis of the source language text to determine its grammatical structure, transfer of the ...
Machine translation enjoyed a fierce research interest during the 1950s and 1960s, which was followed by a stagnation until the 1980s. [7] After the 1980s, machine translation became mainstream again, enjoying an even bigger popularity than in the 1950s and 1960s as well as rapid expansion, largely based on the text corpora approach.
The use of crowdsourcing and text corpus in human-machine translation (HMT) within the last few years have become predominant in their area, [1] in comparison to solely using machine translation (MT). There have been a few recent academic journals looking into the benefits that using crowdsourcing as a translation technique could bring to the ...
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.
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