Within translation/localization we’re all looking to ensure that the quality of the deliverable meets the expectation, in whatever way those two things are defined. Some people may believe achieving that quality is a factor that is inherent in actually doing the work, and builds around the processes. Other people may, however, think of quality as something that can be tested and evaluated after the work is done.
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Globalization and new technology have not left the translation services of the EU institutions untouched. Successive enlargements have more than doubled not only the number of member states but also the number of official languages. The extension and deepening of the European integration have led to more and more different text types being produced and to an ever-increasing translation demand. At the same time, in-house translation staff per language is progressively being reduced. The pressure to provide more, faster and with fewer resources has led to a need to constantly re-think how we carry out the translation work. We all know the buzz words: doing more with less, doing more and better with less, being effective and efficient, doing the right things and doing them right. Increased focus on processes and on making optimal use of technology does lead to efficiency gains. Mostly, however, what saves the situation is an increased use of outsourcing, which implies challenges for the quality assurance.
Can translation service providers and technology providers meet translation buyers’ requests? How can we evaluate the quality of both source and target within the translation process? How do we measure localization processes? These are just few of the questions that passed the review during the roundtable hosted by TAUS in Barcelona on May 12, 2016.
In a recent NPR news piece Uber Plans To Kill Surge Pricing, Though Drivers Say It Makes Job Worth It, Jeff Schneider, engineering lead at Uber describes how they are using machine learning to hack the problem of supply and demand.
I was recently involved in a project to clean up TM pollution, where the target included a lot of translations from a different language variant. I had to work with the internal linguist to prepare a plan to do it in the most efficient way. No matter how many automation tricks I pulled from my hat, the linguist had reservations for them all and it seemed that, quality assurance-wise, nothing could beat running content through a pair of eyes. And yet the cost of manual review was prohibitive; plus one could also argue about the effectiveness of this approach, considering the amount of errors that keep showing up at every stage of a typical translation workflow, where manual review is present everywhere: translation-editing-proofing, client validation, QA/testing.
The question is: are we all on the same evolutionary path? Or do some of us take different turns, make shortcuts and even arrive in different places? The TAUS Executive Forum on April 25 and 26 in Beijing opened new perspectives on translation in China that many of us had perhaps not expected. China typically copies what others have already built and done before them. Fast trains are modeled to the TGV in France, electric cars are inspired by Tesla, and fashion in China follows the trends around the world closely.