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

Cuándo añades un párrafo nuevo a la traducción puedes empezar desde cero o usar una herramienta de traducción automática como punto de partida. Cuándo se encuentre disponible, la herramienta de traducción automática se utiliza por defecto como traducción inicial. A continuación se describen las diferentes opciones, los detalles sobre su disponibilidad, y las consideraciones cuando se utiliza la herramienta de traducción automática.

Opciones para la traducción inicial
Las opciones de "traducción inicial" en la barra de herramientas te permite decidir el contenido inicial de la traducción que se utilizará como punto de partida para cada párrafo. Las opciones disponibles son las siguientes:


 * Utilizar un servicio de traducción automática. Esto permite comenzar la traducción con una versión traducida automáticamente del párrafo original. El número y el nombre de estas opciones puede variar. Las opciones como "Usar Apertium" o "Usar Yandex" están disponibles dependiendo de los idiomas soportados para estos servicios de traducción (más de esto en la siguiente sección).
 * Copiar contenido original El párrafo original será copiado a la traducción. A pesar de que el contenido quedará en el idioma original, algunos de los elementos están adaptados a la wiki de destino. Por ejemplo, los enlaces apuntan al artículo correspondiente en el idioma de destino, y las plantillas serán convertidas en sus equivalentes. Los traductores todavía tienen que reescribir el contenido completamente, pero los elementos adaptados pueden ser más fáciles de reutilizar.
 * Comenzar con un párrafo vacío. Comenzar con un párrafo vacío puede ser de utilidad en casos en que el contenido alternativo requiere más trabajo que simplemente escribiéndolo.

You can quickly switch between the different approaches independently on each paragraph, since each one may work best on different kinds of content. Cambiando entre las diferentes entradas conservan los cambios que hiciste en el párrafo. De este modo, puedes probar una entrada diferente incluso si  empezaste a editar el original sin miedo para perder tus cambios si finalmente decides volver a la entrada original. Dos opciones adicionales son relevantes en este contexto:

It allows you 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.
 * La opción de Reiniciar traducción está disponible cuándo hiciste cambios en el contenido inicial proporcionado. Te permite restaurar el contenido inicial descartando los cambios que hiciste.
 * 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 supports 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 ( languages supported )
 * LingoCloud ( languages supported )
 * Google Translate ( languages supported )
 * Yandex ( languages supported )
 * Youdao ( languages supported )
 * Elia (languages supported)

The lists 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 lists show the language code for the source language at the initial indentation level and the codes of all the supported target languages below it.

Languages are enabled gradually, based on the observed results and community feedback. It is possible that machine translation for some languages 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 helping translation services 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 and 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. Try language models locally with OPUS-CAT (available for Windows)
 * 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, numerals or end of sentence marks (view full list).

Expanding 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 published 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 naturally 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.