So you jumped on the automatization bandwagon and now want to run automatic Quality Assurance (QA) on translations.
The general approach to run automatic QA is to use:
QA tools normally work with bilingual (source and target) files. They help you to find:
To avoid false positives that these QA tools may generate, it’s highly recommended to create special configurations that would be used to automatically reduce the noise. For example, for Verifika it would be a quality profile per project/language.
Though some tools still provide QA reports in Excel sheets, the better way is to utilize the solutions which offer automatic updates of the segments being QAed – right from the report. Otherwise, it takes a lot of time to switch between working environments and implement all the needed changes into the working files.
On August 21 and 22, 280 participants from 16 countries met for the 11th Translation Forum Russia. The conference has been held annually for over a decade, but for the first time it switched to online. Fortunately, the new format didn’t put a damper on the TFR’s usual heated discussions, provocative presentations, and innovative ideas.
Fujitsu is a well-established Japanese information and communication technology company with a global footprint. With Global Delivery Centers (GDCs) in eight countries around the world, the company provides services to over 180 countries and regions, operates in over 40 languages, and helps customers achieve global success.
Webinar: New(ish) applications of AI in content creation and localization When people think of AI use cases in content localization, the first thing that comes to mind is MT for structured content. But there are many other use cases for AI in and around translation that are rapidly gaining traction. In order to stay ahead […]
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