Help:Content translation/Translating/Initial machine translation/fr

Lorsque vous ajoutez un nouveau paragraphe à la traduction, vous pouvez repartir de zéro ou utiliser une traduction automatique comme point de départ. Lorsqu'elle est disponible, la traduction automatique est utilisée par défaut comme traduction initiale. Les différentes options, les détails de leur disponibilité et les considérations relatives à l'utilisation de la traduction automatique sont décrits ci-dessous.

Options pour la traduction initiale
Les options de "traduction initiale" dans la colonne des outils vous permettent de décider du contenu initial à utiliser comme point de départ pour chaque paragraphe. Les options disponibles sont les suivantes :


 * Utiliser un service de traduction automatique. Ceci vous permet de commencer avec une version traduite automatiquement du paragraphe d'origine. Le nombre et le nom de ces options peuvent varier. Des options telles que "Utiliser Apertium" ou "Utiliser Yandex" sont disponibles en fonction des langues prises en charge par ces services (pour en savoir plus, voir la section suivante).
 * 'Copie du contenu original. Le paragraphe d'origine est repris intégralement dans la traduction. Bien que le contenu reste dans la langue originale, certains éléments sont adaptés au wiki ciblé. Par exemple, les liens pointeront vers l'article correspondant dans la langue cible, et les modèles seront convertis en modèles équivalents. Les traducteurs doivent néanmoins réécrire complètement le contenu, mais les éléments adaptés seront plus faciles à réutiliser.
 * Commencer par un paragraphe vide. Commencer par un paragraphe vide peut être utile dans les cas où le nouveau contenu nécessite plus de travail que la simple saisie.

Vous pouvez rapidement passer d'une approche à l'autre indépendamment sur chaque paragraphe, car chacune d'entre elles peut fonctionner au mieux sur différents types de contenu. Switching between the different approaches preserves the changes you made on the paragraph. In this way, you can try a different approach even if you started editing the original one without the fear to lose your changes if you finally decide to go back to the original approach. Two additional options are relevant in this context:

It allows to restore the initial content by discarding the changes you made. It allows to set the default approach for the next paragraphs that are added to the translation. This can be very convenient if you found that a particular translation service works generally better than the default one.
 * The reset translation option is available when you made modifications on the initial content provided.
 * The mark as default option is available when you select an approach for a paragraph that is not the default.

Machine translation availability
Content translation integrates several translation services, and each service support a different set of languages. The services supported are listed below with a link to the list of languages they support:


 * Apertium ( languages supported )
 * OpusMT (langues prises en charge)
 * LingoCloud ( languages supported )
 * Matxin ( languages supported )
 * Google Translate (langues prises en charge)
 * Yandex ( languages supported )
 * Youdao ( languages supported )

The list of languages above point to the configuration code to make sure that the information is in sync with the way the tool currently works. The list show the language code for the source language at the initial indentation level and the codes of all the supported target languages below it.

Language enablement is done in a gradual way based on the observed results and the community feedback. It is possible that machine translation has not been enabled yet, even if they are supported by the underlying services.

Improving existing translation services
When you publish a translation with Content Translation you are already helping translation services to improve. All the corrections you make to the initial machine translations are exposed through an API and data dumps and can be potentially used to improve existing services. In addition to that, some of the translation services listed above provide specific ways you can contribute to their projects.

OpusMT
OpusMT is an open source neural machine translation system that is trained with multilingual documents freely licensed available online. This open corpus is used to train the translation system, and expanding the corpus will lead to better translations. The contents generated by using Content Translation are integrated automatically in the corpus, but you can contribute to expand the corpus further:

You can upload translated documents in various formats including translated webpages to be incorporated to the corpus.
 * Propose new sources to be integrated in the open corpus. You can contact Jörg Tiedemann to propose a new data source to expand the corpus.
 * Submit documents directly (still a preliminary prototype).

OpusMT is based on MarianNMT which is also an open source project. People with technical knowledge and interested in machine learning can also contribute to improve it.

Apertium
Apertium is an open source rule-based translation system. You can contribute to the project by encoding the language rules of your language. This process requires both linguistic and advanced technical knowledge, but you can get support from the Apertium team to expand the translation support for a new language pair.

Google Translate
Google Translate is not an open source project, but there are still ways for users to contribute back:


 * Join the Google Translate Community to provide translations that help train their system.
 * Report bugs when the translation system shows unexpected behavior when dealing with certain elements such as spacing or end of sentence marks (view full list).

Expanding the language support with new translation services
Content translation has been designed as an extensible platform. So it is possible to develop new clients to integrate additional translation services. Some considerations about the way translation services are integrated:

No personal information is shared with the translation services.
 * Machine translations and the user corrections made are publicly as part of the data on published translations, which can provide a useful resource to create or improve your translation service.
 * External services integrated only receive publicly available wiki content, and return a translated version of such content that is compatible with the licenses used in the wiki.

Feedback on the support provided for each language is very useful. Please, let us know if you are missing support for some language, or whether higher quality options are available for it. You can provide such feedback on the project talk page or in this ticket.

Considerations on machine translation
Machine translation is far from perfect when intended as a final outcome. However, many users find it very useful as a starting point. Please make sure to review the content from these different perspectives:


 * Make sure the original meaning is preserved.
 * Check that there is no information missing, especially for elements such as links, references and templates that include information that is not always visible on the surface.
 * Read the translated content to make sure it reads natural as an independent page.

Limitations with complex elements
In some cases the content may not appear in the translation as expected:

This means that formatting and rich content elements such as links and citations from the original article are lost in the translation, and Content translation needs to guess where those belong in the translated text. Re-adding those elements is not always perfect and some elements may be in the wrong position or applied to the wrong part of the text. Make sure to review the contents inside those elements to make sure there is no important information missing.
 * Some of the services supported only work with plain text.
 * Complex elements such as references or templates may use a different structure in each language, which makes it hard to transfer the content from one language into the other.

Enforcing the review of machine translation
Several automatic mechanisms exist to enforce the review of the initial contents. In this way, the tool makes sure that the initial automatic translation is reviewed enough before the contents get published.