In the framework of my Industrial PhD, and after some experience in two Language Service Providers (LSP), I wanted to understand why so many language professionals refuse MTPE projects, or when they accept them, why the LSP or end customer is ultimately dissatisfied with the quality of the product. To address these issues and clarify MTPE needs in the globalization market, I designed an online questionnaire using Jotform. ‘Machine Translation & Post-Editing in the Industry’ was aimed at European LSPs and received 66 valid responses. It was completed in February 2019.
I have a very clear memory of the moment in 2006 when the proverbial light bulb went off in my head and I first understood the idea that machine translation (MT) could be used in some other way than as a production tool for translators. The bulb was sparked by an article by Jaap van der Meer in the newsletter of the Center for Information-Development Management.
Let’s face it: the reality of the daily work in our industry, the processes and text types we encounter lead to situations where many translators eventually run the risk of losing their ability to translate freely and creatively.
The translation world is changing fast. New technologies appear all the time: neural translation, adaptive translation, rule-based translation, statistical machine translation, adaptive neural translation… it can be hard to keep up. More and more, companies are using these tools in a bid to improve productivity, but the quality of their output still needs to be checked in the old-fashioned, human way. Hence post-editing has become a specialized skill and a crucial step in the translation process. As an English to French translator who loves pretty sentences, I wasn’t sure this would be a task I would enjoy. However, when TAUS asked me to review their post-editing course, I decided it was time to find out more. It is part of the TAUS e-learning platform, which offers courses, but also lots of useful downloadable resources and forums that they’re hoping to expand.