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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.
DeepL for Windows translating from Polish to French. The translator can be used for free with a limit of 1,500 characters per translation. Microsoft Word and PowerPoint files in Office Open XML file formats (.docx and .pptx) and PDF files up to 5MB in size can also be translated.
This dataset can contain documents in many languages, but is in practice dominated by English text. [36] After this pre-training, they are fine-tuned on another task, usually to follow instructions. [39] Since they are not trained on translation, they also do not feature an encoder-decoder architecture.
When Google Translate generates a translation proposal, it looks for patterns in hundreds of millions of documents to help decide on the best translation. By detecting patterns in documents that have already been translated by human translators, Google Translate makes informed guesses (AI) as to what an appropriate translation should be. [105]
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%).
Google Translate's NMT system uses a large artificial neural network capable of deep learning. [1] [2] [3] By using millions of examples, GNMT improves the quality of translation, [2] using broader context to deduce the most relevant translation.
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