The present and future of Linguistic Quality Assurance (LQA) In these times of global brands and localized marketing, what is translation quality? Like many other concepts where translation is involved, it depends on the context.
There was a time when quality assurance was considered equally important to the translation itself. After every translation was completed, it was expected that at least one reviser or proofreader would go over it before publication. There was also a time when quality managers didn’t exist. Any project manager would be tasked with finding those more glaring formatting, layout, or even branding errors that might have slipped through, even when they didn’t know anything about the target language. We can say those times are long gone. The explosion of both static and (mostly) dynamic content for over a decade now has meant that there is no time to do quality assurance on every piece of translation before it’s published. With more content being produced every year, the position of quality manager has evolved out of the necessity for greater oversight and control over complex production and localization workflows. What does this mean for translation quality itself? Quality standards were developed as a result of long and painstaking industry collaborations, and the idea of “fitness for purpose” became a functional compromise for both buyers and service providers: we can use a quality standard to find exactly where the errors are, but if the translation is fit-for-purpose then maybe we don’t need to assign all the resources needed to get a near-perfect translation There has also been a parallel development in the technology used for quality assurance, i.e. for the process designed to match the translation to the quality standards. There are now more quality assurance (QA) tools for translation and localization than ever before, both stand-alone and built-in within CAT tools. Put together, they have created a false sense of security (and also unrealistic expectations) — a sense that we have at our disposal the means to identify and fix anything and everything that might be wrong in a translation. Another common myth is that perhaps we can even do all that without the need of a human reviser. Whether we look at stand-alone QA tools that linguists can use to validate and improve on the quality of a translation, or we consider the QA modules one can find embedded in CAT tools, there are some obvious inherent disadvantages that over time have made them rather unpopular. By extension, they have made the QA process as a whole a box-ticking exercise that normally comes as an afterthought. These QA tools were intended to automate the process of quality assurance in post-translation and help revisers and proofreaders find errors and apply corrections in a translation — which is exactly what you want to have, ideally. The problem with such language-agnostic QA tools is that by far most of the warnings they will produce are in fact false positives, in other words the warnings are pointing to issues that are not actual errors. Revisers have been using these tools for many years,