Microsoft announces ‘historic milestone’ and has developed Artificial Intelligence that can translate Chinese News to English as accurately as any human.
According to the Microsoft blog, researchers at the company’s US and Asian labs believe they have created the first machine translation system that can accurately translate sentences of news articles from Chinese to English with the same quality and accuracy as a person, and therefore without any of the cliches typically experienced and shared numerously online over the years.
Xuedong Huang, a technical fellow in charge of Microsoft’s speech, natural language and machine translation efforts, said the new AI would set a significant milestone in one of the most challenging natural language processing tasks.
“Hitting human parity in a machine translation task is a dream that all of us have had,” Huang said. “We just didn’t realize we’d be able to hit it so soon. The pursuit of removing language barriers to help people communicate better is fantastic,” he said.”It’s very, very rewarding.”
Arul Menezes, a manager in Microsoft’s machine translation team, said the team set out to prove that its systems could perform about as well as a person when it used a language pair – Chinese and English – for which there is a lot of data, on a test set that includes the more commonplace vocabulary of general interest news stories.
Accurate translation between Chinese and English languages is a lucrative business, and the resultant success will make it easier for companies to do business and communicate better with their Chinese counterparts, as well as giving Microsoft a competitive edge over other companies making translation software.
Menezes said the research team can apply the technical breakthroughs they made for this achievement to Microsoft’s commercially available translation products in multiple languages. That will pave the way for more accurate and natural-sounding translations across other languages and for texts with more complex or niche vocabulary. “Given the best-case situation as far as data and availability of resources goes, we wanted to find out if we could actually match the performance of a professional human translator,” and it seems, they have.