Like any project management workflow, managing your organization’s translation and localization is a constant balancing act between speed, quality and price. In a recent webinar, “Translation Trends 2015” hosted by MemSource, Microsoft Translator’s Group Program Manager Chris Wendt showed how improvements in collaboration technology for translation could help raise the bar for all three of these elements.
The primary choice faced by businesses when deciding to translate their content is whether to use human or machine translation to accomplish the task. To date, human translation has been able to provide high quality translation, but at a slower speed and higher cost than machine translation. In contrast, machine translation is instantaneous and inexpensive, but can be less accurate than human translation.
Many organizations have had great success using machine translation with human translation integrated into their post-editing workflows — it has been shown to lead to productivity increases of up to 25%. Integrating human translation into post-publishing workflows using the latest collaborative translation memory software can have an even greater impact.
Post-publishing translation allows website owners to leverage their community to refine the output of machine and human translation. This community includes subject matter experts, enthusiasts, employees, and other professional translators. In a recent research study at the University of Illinois at Urbana-Champaign, it was shown that the quality of machine translation, when interpreted by a subject matter expert, is of higher quality than human translation when that translator is not an expert in the field.
Using a post-publish, post-edit workflow, organizations can raise the bar in speed, quality, and price— translation is done faster than by human translation, is of higher quality than machine translation alone, and decreases the cost of dedicated human translation services. For your post-publish, post-edit workflow to be successful, your organization needs to have several elements in place. The first is a machine translation API such as Microsoft Translator. This provides the initial translation used for your content. The second is a collaborative translation framework or translation memory system. This will allow you to coordinate your body of contributors to the translation project. Lastly, you will need to provide training for using these assets— making sure to include subject matter experts as well as translators.
To learn more about post-publish, post-edit translation, and to see presentations from Microsoft Translator‘s Chris Wendt, MemSource CEO David Canek, Torben Dahl Jensen from TextMinded, and Moravia‘s Jan Hofmeister click on the link below.