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Kural translations by language. v. t. e. Machine translation is use of computational techniques to translate text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages. Early approaches were mostly rule-based or statistical.
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. It is the dominant approach today [1] : 293 [2] : 1 and can produce translations that rival human translations when ...
The Language Technologies Institute (LTI) is a research institute at Carnegie Mellon University in Pittsburgh, Pennsylvania, United States, and focuses on the area of language technologies. The institute is home to 33 faculty with the primary scholarly research of the institute focused on machine translation, speech recognition, speech ...
Translation Research Group: Academic: Provo, United States: British Computer Society: Natural Language Translation Specialist Group: Academic: Swindon, England: Carnegie Mellon University: Language Technologies Institute: Academic: Pittsburgh, United States: Center for the International Cooperation for Computerization: Machine Translation ...
History of machine translation. 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.
GNMT improved on the quality of translation by applying an example-based (EBMT) machine translation method in which the system learns from millions of examples of language translation. [2] GNMT's proposed architecture of system learning was first tested on over a hundred languages supported by Google Translate. [ 2 ]
A typical way for lay people to assess machine translation quality is to translate from a source language to a target language and back to the source language with the same engine. Though intuitively this may seem like a good method of evaluation, it has been shown that round-trip translation is a "poor predictor of quality". [1]
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.