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As of 2018, all supported memoQ editions contained these principal modules: File statistics Word counts and comparisons with translation memory databases, internal content similarities and format tag frequency. memoQ was the first translation environment tool to enable the weighting of format tags in its count statistics to enable the effort involved with their correct placement in translated ...
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [ 1 ] [ 2 ] Like the original Transformer model, [ 3 ] T5 models are encoder-decoder Transformers , where the encoder processes the input text, and the decoder generates the output text.
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.
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]
Name Supported File Formats OS Language Widget tool License Across Language Server [2]: Microsoft Word (DOC, DOT, DOCX, and DOCM files), Microsoft Excel (XLS files, and XLSX and XLSM files), Microsoft PowerPoint (PPT and PPS files as well as PPTX, PPSX, and PPTM files), Rich Text Format1 (RTF files), text files (TXT files), TeX (TEX files), HTML, XHTML, XML, SGML, Adobe FrameMaker (in MIF ...
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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