Content translation/Machine Translation/MinT

MinT (Machine in Translation) is a translation service based on open source neural machine translation models. The service is hosted in the Wikimedia Foundation infrastructure and will be part of the list of machine translation (MT) systems available for users of Content Translation and other Wikimedia projects. The translations provided are based on [ https://ai.facebook.com/research/no-language-left-behind/ NLLB-200], [ https://opus.nlpl.eu/ OPUS], [ https://ai4bharat.iitm.ac.in/indic-trans2 IndicTrans2] and [ https://github.com/Softcatala/nmt-models Softcatalà] translation models which have been optimized for performance using [ https://github.com/OpenNMT/CTranslate2 OpenNMT Ctranslate2 library] in order to [ https://techblog.wikimedia.org/2020/04/06/saying-no-to-proprietary-code-in-production-is-hard-work-the-gpu-chapter/ avoid the need for GPU acceleration]. For more details you can check the source code, the [ https://translate.wmcloud.org/api/spec API spec], and [ https://translate.wmcloud.org/ a test instance].

Key features

 * No nonpublic personal information of users is sent to MinT. The MT system will be accessed via an API.  Article content (freely licensed) is sent to the MinT server and no direct communication is happening between the user and external services and no nonpublic personal information of users (IP, username) is sent to the MinT service.  The client contacting MinT is open source and you can [ https://github.com/wikimedia/mediawiki-services-cxserver/blob/master/lib/mt/MinT.js check its source code].  Although the MinT service is hosted in Wikimedia infrastructure, the integration follows the same pattern as other external services (please also see a diagram of this technical setup at the end of the section).
 * Any copyrightable information is returned from MinT under a free license. When MinT is used, a translated version of Wikipedia content is obtained.  The copyrightability of such machine-generated content is an open legal question.  To the extent that MinT translations are copyrightable, these translations are available under the same free license as the Wikipedia content being translated.  Users can modify it and publish it as part of Wikipedia without conflicts with existing policies.  The resulting content translated by MinT and the user modifications will be available under the same license that is used for the rest of the articles in Wikipedia.
 * Benefits the wider open source translation community. Translations obtained from MinT and user modifications will be publicly available. The post-edited translations are of special interest for the translation research community who can use this resource to create new translation services to support languages for which open source machine translation is not available yet. This will help developers create and improve machine translation systems.
 * Users can disable it. Automatic translation is an optional tool in Content Translation. Users have an option to disable it if they don't find it useful for some reason. Although many Content Translation users have requested for translation services, each individual user eventually decides whether they would like to use them or not.

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Questions about this service
We have addressed some immediate questions about MinT in this section. This is also available in the Content Translation FAQ page.

What languages are being handled by MinT? Are there plans to add more?
MinT is designed to host multiple open translation models. The number of languages supported will depend on them. The list of machine translation (MT) systems available will include the most up-to-date list.

How is using MinT different than using Apertium or others?
As a user of Content Translation you will not feel any difference on the translation interface as MinT will display the translated content in the same way Apertium or other services currently do for the supported language pairs. Different services provide a different translation quality level depending on the language and the specific contents. You can try and change among the available services the one providing the best initial translation for a given paragraph.

How is the machine translation being done if I choose MinT?
When a user starts translating an article, the HTML content of each section of the source article is sent to MinT. The MinT service processes the request and uses one of the translation models available based on the supported language and configuration. A translated version is obtained and displayed on the respective translation column of Content Translation. Links and references are adapted as usual and users can modify the content as required.

This process continues for all the sections of the article being translated. For better performance, the translations for consecutive sections are pre-fetched. The user can save the unpublished translation (to work on it again at a later time), revise, or publish the article in the usual manner. The article is published on Wikipedia like any other normal article with appropriate attribution and licenses.

Here’s a diagram of the process.

Is MinT based on open source software?
The MinT service is open source and it integrates models that are released as open source:


 * The AI research team at Meta [ https://github.com/facebookresearch/fairseq/tree/nllb released the translation models used by NLLB-200 with an open source license] and [ https://huggingface.co/datasets/allenai/nllb the dataset used for training] as part of the [ https://ai.facebook.com/research/no-language-left-behind/ No Language Left Behind project].
 * The [ https://opus.nlpl.eu/ OPUS project] provides pre-trained [ https://github.com/Helsinki-NLP/OPUS-MT neural translation models trained on OPUS data with an open source license].

These models have been optimized for performance using [ https://github.com/OpenNMT/CTranslate2 OpenNMT Ctranslate2 library] which is also an open source library.

Content Translation evolved from a long-standing need to bridge the gap in the amount of content between Wikipedias in different languages. Like all other software used on Wikimedia sites, Content Translation is also open source. In this particular case as well, we are using an [ https://github.com/wikimedia/mediawiki-services-cxserver/blob/master/lib/mt/MinT.js open source client] to interact with the external service and import freely licensed content in order to help users expand our free knowledge. To use MinT we are not adding any proprietary software in the Content Translation code, or on the Wikimedia websites and servers.

Should I be worried about my personal information when using MinT?
Irrespective of the service being used, you can be sure that only Wikipedia content from existing articles is sent and only freely licensed content will be added back to the translation. Communication with those services happens at the server side, so they are isolated from the user device and they have no access to nonpublic personal information of users. Please refer to this diagram for more details.

What if MinT is the only machine translation tool available and I don't want to use it?
Machine Translation is an optional feature in Content Translation that you can easily disable at will. If more machine translation systems are added for your languages, you can choose to enable MT again and select the MT service of your choice.

Will the content translated by MinT be free for use in Wikipedia?
Yes. The content received from MinT is otherwise freely available on the web translation platform. For ease of use Content Translation receives it via an API to make it seamlessly available on the translation interface. This content can be modified by the users (if necessary) and used in Wikipedia articles under free licenses.

Can this content be used for improving machine translation systems in general?
Yes. Translations made in Content Translation are saved in our database. This information will be made publicly available for anyone to use as translation examples to improve their translation services (from University research groups, open source projects to commercial companies, anyone!). The content can be accessed via the Content Translation API. Please note, only information related to translated text is publicly available. This includes – source and translated text, source and target language information and an identifier for the segment of text.