The big breakthrough in digital language translation

Google neural machine translation (GNMT)

Many of you may already rely on Google Translate to get quick, relatively accurate translations, perhaps for Spanish or Chinese documents into English—now offering broad support for 130 languages.

The accuracy of Google’s translation software was given a giant boost in September of 2016 with the introduction of Google Neural Machine Translation (GNMT) technology. Based on the latest advances in artificial intelligence machine learning, it enables ‘zero-shot translation,’ i.e., translation of languages never before seen by the Google Translate—for example, Japanese to Korean when the system ONLY has information about English to Japanese and Korean. –This helped reduce translation errors by up to 90%. GNMT is moving at a steady pace in 2017 to upgrade all Google Translate systems for different language pairs.

When NOT to rely on digital translation technology

Over a year ago I posted an Insights article comparing Google Translate to other translation options at the time. My advice remains essentially the same—i.e., when you are dealing with important contractual or legal matters it pays to invest in the services of a professional translator (human). Only then will you gain a full understanding of the stylistic, syntactical and other nuances of the originating language.

However, as the world grows smaller, even small companies require immediate access to information across linguistic boundaries to stay on the same page with their global partners. Basic translation software, like Google Translate, as well as other standard options, e.g., Babylon, LEC’s Power Translator, and Promt, can help a business manager quickly grasp the import of any email, document, or website. Whether free or pay-for-service, these options work inside Microsoft Suite formats to convert docs– many of them offering text-to-speech capabilities, spell check, and pronunciation features.

GNMT’s brilliant zero-shot translation breakthrough

GNMT is modeled after neuronal connections within the human brain. It is similar to deep learning technology that identifies commands spoken into Apple and Android devices and allows for digital facial recognition.

GNMT advances the accuracy and speed of AI-enhanced translations in the following ways—

  • It offers both long and short-term digital memory to enhance recognition of semantical patterns. It understands sentences and larger word groupings, a giant leap forward over the more limited translations derived from individual words/phrases.
  • Its deep learning capability allows it to pick up subtleties of language similar to how Siri ‘understands’ us better over time.
  • GNMT translation leverages Google’s tensor processing units, designed specifically for AI computing, resulting in much faster processing.
    Following Google’s lead, Microsoft and Baidu are also working to develop networks modeled after human neural networks that more accurately and efficiently understand and respond to human language.

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