Without revealing names, the organizers said the four professional translators scored better in translating random English articles -- literature and non-literature -- into Korean and other Korean articles into English than the machines.

Of the machines, Google scored a total of 28 out of 60, followed by Naver's automated translation app called Papago with 17 and Systran with 15, the tech company officials with knowledge of the matter said.

"Google's translation level was quite surprising," an industry official who participated in the event said on the condition of anonymity. "It looked like Systran scored the lowest as the company specializes in business translation."

Automatic translation programs using machines have improved recently thanks to the introduction of the technology called the neural machine translation. Major tech giants including Google and Naver rolled out various NMT services last year.

The NMT system is based on a deep learning framework that learns from millions of examples from over 100 different languages.

Unlike previous machine translations that were adopted 10 years ago, the new system considers an entire sentence as one unit.

Previous systems independently translated words and phrases within a sentence. (Yonhap)