It was a real delight listening to Kirti Vashee from Asia Online presenting on the ROI of Machine Translation – Scoping and Measuring MT. It took place at the most recent annual Association of Language Companies conference in New Orleans between May 16-20, 2012.
Much of the today’s online content is dynamic and continuously flowing. The need for real time in-language content cannot be met by human translators alone due to cost and time restraints.
Machine translation (MT), especially statistical machine translation is gaining traction among enterprises that have large amounts of data to translate. IT companies and travel review sites are examples of early adopters of statistical MT.
Compared to any general or free MT tools out there such as Google, a tool like Asia Online is highly customizable. It gives clients much more control on terminology, non-translatable terms, vocabulary choice and writing style. As a result, it produces much higher accuracy and translation quality, especially in highly specialized domains.
This echoes the feedback I heard from one of wintranslation’s enterprise clients who has been using statistical MT for the last few years. Our translation team have been tasked with post editing, providing corrective feedback to the MT engineering team for continuous improvements.
Post editing raw output is a different skills set than traditional editing of human translations. Post editors must understand the weakness of statistical MT systems (i.e. word order needs to be switched sometimes).The more post editors recognize the pattern, the more efficient they become and also much less frustrations.
There is a real and imminent opportunity for translation companies to offer real-time translation services for select type of content that is out of reach for human translations due to time and cost. The linguistic training of statistical translation engines and developing post MT editors are key pieces in realizing that opportunity.