Quality used to be a static concept in the translation industry. One quality would fit all purposes, all audiences and all content. Now, we see much more differentiation in output of content. Marketing messages require a lot of care and tuning to the persona in question, while support articles need to be put out fast and easy with tolerance for fluency errors. Many language service providers already support two, three or more levels of quality. But how do you manage that? The TAUS Quality Dashboard with the underlying DQF/MQM metrics is getting traction as a standard approach to quality evaluation. It can help to differentiate, measure and benchmark translation quality according to content profiles. It takes a lot of the subjectivity out of the quality management function. Besides, DQF makes reporting on quality and productivity of translation very easy and efficient and it helps to aggregate data that support decisions on the selection of resources, tools and processes. In this session, you will hear different perspectives from companies working with DQF — either through an integration with their computer-assisted translation tool, from a user perspective and from adopting the DQF/MQM metrics model.
Translation Quality Evaluation with DQF and the TAUS Quality Dashboard