What do Wordpress, Linux, and Firefox all have in common? All of these successful projects are the result of crowdsourced contributions. As the Internet continues to connect us, collaborating on projects has become easier than ever. Even in the localization industry, crowdsourced translation solutions are helping to make translation services available to everyone and the advent of new technologies has brought about a few different methods of collaborative translation projects. Let’s take a look at three of the most popular models of crowdsourced translations.
Translation memory is an important tool in the modern translator’s toolkit, and one that is currently the focus of a great deal of discussion in the translation and localization community. Simply put, translation memory is a type of shared database that stores translations and continually updates itself as its users work.
What is TM and why does it always come up when talking about translation services? Known as translation memory, TM first commercially appeared in the early 1990s and has since played a crucial role in translation efficiency and helping businesses go global. Translation memory is essentially a linguistic database that stores previously translated sentences, phrases, and words into a system that allows translators to translate content more efficiently and consistently across projects.
Even when human societies first tentatively interacted with each other, there were instances of interpretation and translation. Reasons such as trade and diplomacy between nations and societies were important early engines behind the refinement of translation practices, and the urge to better understand other viewpoints all involved different kinds of evolving methods.
Machine translation as a concept has come a long way since it was initially tested over 60 years ago. It was originally suggested as a method for the US government to monitor Russian activities after World War 2; now it has developed into something that has transformed the translation industry entirely.