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Neural machine translation. 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 ...
t. e. Google Neural Machine Translation (GNMT) was a neural machine translation (NMT) system developed by Google and introduced in November 2016 that used an artificial neural network to increase fluency and accuracy in Google Translate. [1][2][3][4] The neural network consisted of two main blocks, an encoder and a decoder, both of LSTM ...
A deep learning-based approach to MT, neural machine translation has made rapid progress in recent years. However, current consensus is that the so-called human parity achieved is not real, being based wholly on limited domains, language pairs, and certain test benchmarks [ 24 ] i.e., it lacks statistical significance power.
Google Translate is a web-based free-to-use translation service developed by Google in April 2006. [12] It translates multiple forms of texts and media such as words, phrases and webpages. Originally, Google Translate was released as a statistical machine translation (SMT) service. [12] The input text had to be translated into English first ...
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.
DeepL Translator is a neural machine translation service that was launched in August 2017 and is owned by Cologne -based DeepL SE. The translating system was first developed within Linguee and launched as entity DeepL. It initially offered translations between seven European languages and has since gradually expanded to support 33 languages.
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 ...
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]