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Weblate is an open source web-based translation tool with version control. It includes several hundred languages with basic definitions, and enables the addition of more language definitions, all definitions can be edited by the web community or a defined set of people, as well as through integrating machine translation, such as DeepL Translator, Amazon Translate, or Google Translate.
Many translators use the toolkit directly, to do quality checks and to transform files for translation. Further there are and have been several indirect users of the Translate Toolkit API: Pootle - an online translation tool; open-tran - providing translation memory lookup (was shut down on January 31, 2014.) [3]
A translation management system (TMS), formerly globalization management system (GMS), is a type of software for automating many parts of the human language translation process and maximizing translator efficiency. The idea of a translation management system is to automate all repeatable and non-essential work that can be done by software ...
Google Translate is a multilingual neural machine translation service developed by Google to translate text, documents and websites from one language into another. It offers a website interface, a mobile app for Android and iOS, as well as an API that helps developers build browser extensions and software applications. [3]
(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. The Moses site provides links to training corpora.) This is not an all-encompassing list. Some applications have many more language pairs than those listed below.
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. The result is then rearranged and adapted to approach grammatically based human language. [1]
The system constructs the dictionary of single-word translations based on the analysis of millions of translated texts. In order to translate the text, the computer first compares it to a database of words. The computer then compares the text to the base language models, trying to determine the meaning of an expression in the context of the text.
To handle the case where the same original-language text can have different meanings, gettext has functions like cgettext() that accept an additional "context" string. xgettext is run on the sources to produce a .pot (Portable Object Template) file, which contains a list of all the translatable strings extracted from the sources.