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Rosetta is a dynamic binary translator developed by Apple Inc. for macOS, an application compatibility layer between different instruction set architectures.It enables a transition to newer hardware, by automatically translating software.
MateCat ("Machine Translation Enhanced Computer Assisted Translation") is a 3-year research project (Nov 2011 – Oct 2014) funded by the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement No. 287688. [1] It has received over €2,500,000 of European funds. [2]
The following table compares the number of languages which the following machine translation programs can translate between. (Moses and Moses for Mere Mortals allow you to train translation models for any language pair, though collections of translated texts (parallel corpus) need to be provided by the user.
A number of computer-assisted translation software and websites exists for various platforms and access types. According to a 2006 survey undertaken by Imperial College of 874 translation professionals from 54 countries, primary tool usage was reported as follows: Trados (35%), Wordfast (17%), Déjà Vu (16%), SDL Trados 2006 (15%), SDLX (4%), STAR Transit [fr; sv] (3%), OmegaT (3%), others (7%).
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 .
Reverso has been active since 1998, with the aim of providing online translation and linguistic tools to corporate and mass markets. [3] [4] In 2013 it released Reverso Context, a bilingual dictionary tool based on big data and machine learning algorithms. [5] In 2016 Reverso acquired Fleex, a service for learning English via subtitled movies.
As a rule, a universal translator is instantaneous, but if that language has never been recorded, there is sometimes a time delay until the translator can properly work out a translation, as is true of Star Trek. The operation of these translators is often explained as using some form of telepathy by reading the brain patterns of the speaker(s ...
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]