Learn how to evaluate, create and manage a multilingual knowledge base to support international users and customers in multiple languages.
According to Wikipedia, multilingual relates to multilingualism and indicates the use of more than one language. So a multi lingual knowledge base holds content of at least two languages or even more.
From the end users perspective, all content of the knowledge base should be available in his or her language. It is expected to see all necessary articles and resources (as images and pdf files) in the requested language in the latest version. If the user accesses the documentation portal, it should be automatically detect the language and show the content in this locale.
If a new feature is added to the product, the documentation should be available not only in the primary language but also all other supported languages.
For the editor of the knowledge base, it should be easy to add new translations in multiple languages and see at a glance which articles and content are not yet translated yet.
Creating and initializing the localization of a multilingual knowledge base depends mainly on the used software. Normally it can be sum up with the following three steps:
Of course, this just a short summary. The translation of the knowledge base articles can be done in-house, e.g. from a member of the support team, or a product manager that speaks the foreign language.
Many of the existing support suites on the market include a documentation tool to create and run a knowledge base. Depending on the requirements of the Instruction Manager, this is a good and quick solution to use for the user manuals and knowledge base.
But handling multilingual knowledge and content is mostly only a small feature, if at all. For example, Zendesk and Freshdesk allow the creating of multi-language content, but the handling might not be perfectly suited to manage localized content.
If you have the possibility to choose a specific knowledge base or documentation product, the following criteria could be helpful:
Current, state of the art machine translation products as e.g. Google translate or other providers as Microsoft Azure have been improved a lot in the last years.
Computer-generated translation of articles and knowledge base entries is quite good and can be helpful e.g. for a initial translation draft that is reworked and finished by a human.
Since the development of artificial intelligence of such systems is getting better every day, it might only take a few years to fully replace the guilds of human translators.
Some of the limitations are handling of specific domain knowledge that might not always be detected and used by translation applications.
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