Sam Wong writes for New Scientist about an interesting development in the rapidly improving Google Translate:
Traditional machine-translation systems break sentences into words and phrases, and translate each individually. In September, Google Translate unveiled a new system that uses a neural network to work on entire sentences at once, giving it more context to figure out the best translation. This system is now in action for eight of the most common language pairs on which Google Translate works.
Although neural machine-translation systems are fast becoming popular, most only work on a single pair of languages, so different systems are needed to translate between others. With a little tinkering, however, Google has extended its system so that it can handle multiple pairs – and it can translate between two languages when it hasn’t been directly trained to do so.
For example, if the neural network has been taught to translate between English and Japanese, and English and Korean, it can also translate between Japanese and Korean without first going through English. This capability may enable Google to quickly scale the system to translate between a large number of languages.
“This is a big advance,” says Kyunghyun Cho at New York University. His team and another group at Karlsruhe Institute of Technology in Germany have independently published similar studies working towards neural translation systems that can handle multiple language combinations.
Google’s researchers think their system achieves this breakthrough by finding a common ground whereby sentences with the same meaning are represented in similar ways regardless of language – which they say is an example of an “interlingua”. In a sense, that means it has created a new common language, albeit one that’s specific to the task of translation and not readable or usable for humans.
Thanks, Kobi! And anyone interested in how GT got as good as it is should read this NY Times Sunday Magazine piece by Gideon Lewis-Kraus, which explains it in the context of the whole “artificial intelligence” phenomenon — long, but well worth it.