Translation

wE use AI to help with localization project management. They can automate content creation and translation when possible, and monitor workflows to ensure that quality remains high while meeting cost and time milestones.

Think of AI translation as a way to make human translators smarter and projects easier to manage. Both are great news for companies seeking to localize their content.

Not all translation tasks are suited to AI translation tools. As we noted earlier, projects characterized by high levels of complexity and technical language are less suited. Legal and scientific terms can pose unique challenges to machine learning systems, and skilled humans will generally perform more reliably.

Human translation involves using human professional translators, whereas machine translation is run through computer software with no human involvement. In many cases, the best translation is a combination of human and machine translation: the software produces a first pass at the translation, and then human translators review and refine the translation. That translation is then fed back into our translation memory (TM) software to be applied to future projects.

A common misconception is that our machine translation (MT) engines work just like our translation memories (TM). While the latter is updated automatically at the end of each project to be reused for subsequent projects, the former requires manual intervention for improvement and enhancement. For most MT-powered projects, we use both our MT engines and translation memories in tandem to achieve optimum translation quality and savings.