Assertion: neural machine translation | /r/HasProperty | nmt
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text: Neural Machine Translation (NMT)
text: Neural Machine Translation (NMT)
text: The Neural Machine Translation (NMT) technology: higher accuracy, fluency and integration of the whole context of the sentence
text: The advent of Neural Machine Translation (NMT) caused a radical shift in translation technology, resulting in much higher quality translations.
text: 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.
text: Neural machine translation (NMT) is not a drastic step beyond what has been traditionally done in statistical machine translation (SMT).
text: In September 2016, a research team at Google announced the development of the Google Neural Machine Translation system (GNMT) and by November Google Translate began using neural machine translation (NMT) in preference to its previous statistical methods (SMT) which had been used since October 2007, with its proprietary, in-house SMT technology.
text: Neural machine translation (NMT) reduces post-editing effort by 25%, outputs more fluent translations, and “linguistically speaking it also seems in quite a few categories that it actually outperforms statistical machine translation (SMT).
text: Their work can be treated as the birth of the Neural Machine Translation (NMT), which is a method that uses deep learning neural networks to map among natural language.
text: Bearing these factors in mind, it’s no surprise that deep learning recently kicked up a storm in translation and localization to create what we now know as Neural Machine Translation (NMT).
text: Attention mechanisms are being increasingly used to improve the performance of Neural Machine Translation (NMT) by selectively focusing on sub-parts of the sentence during translation.
text: In this issue of step-by-step articles, we explain how neural machine translation (NMT) works and compare it with existing technologies: rule-based engines (RBMT) and phrase-based engines (PBMT, the most popular being Statistical Machine Translation – SMT).
text: It is a general agreement that Neural Machine Translation (NMT) has surpassed Statistical Machine Translation (SMT) in terms of fluency and adequacy when humans read the texts produced by the software.
text: Neural machine translation (NMT), directly models the mapping of a source language to a target language without any need for training or tuning any
text: The Encoder-Decoder architecture with recurrent neural networks has become an effective and standard approach for both neural machine translation (NMT) and sequence-to-sequence (seq2seq) prediction in general.
text: Neural machine translation (NMT) directly models the mapping of a source language to a target language without any need for training or tuning any component of the system separately.
text: Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, with the potential to overcome many of the weaknesses of conventional phrase-based translation systems.
text: Neural Machine Translation (NMT) is the new standard for high-quality AI-powered machine translations.
text: As is usual with general deep learning, neural machine translation (NMT) does not rely on pre-designed feature functions.
text: Thanks to a shift in technology, there has been a quantum leap in machine translation quality in recent times: neural machine translation (NMT) outperforms statistical machine translation (SMT) in a wide range of set-ups and language pairs.
text: Neural Machine Translation (NMT):
text: Most recently, there’s been quite a bit of talk about Neural Machine Translation (NMT), a new method that uses Deep Learning to translate foreign language texts.
text: He previously led Microsoft Translate’s transition from phrase-based translation to neural machine translation (NMT) as a Principle Research Scientist at Microsoft Research from 2014 to 2017.
text: Most significantly in 2017, Google moved away from Phrase-Based Machine Translation (PBMT) and was replaced by Neural Machine Translation (NMT).
text: Neural Machine Translation (NMT) is an exciting and promising new approach to Machine Translation.
text: First of all, neural machine translation (NMT) is not a drastic step beyond what we have traditionally done in statistical machine translation (SMT).
text: It is clear that Neural Machine Translation (NMT) is yet another step up and a very promising technology.
text: There are a number of approaches to this, including statistical machine translation (SMT) based on parallel translation data, and neural machine translation (NMT) that uses deep learning technology, but our main area of expertise is a rule-based (RBMT) engine.
text: Natively Neural – Use modern neural machine translation (NMT) as default for all supported languages.
text: Within a year neural machine translation (NMT) had replaced statistical machine translation (SMT) as the state of the art.