Google has announced a Neural Machine Translation (NMT) system for improved translation. The NMT is said to reduce translation errors across its Google Translate service by between 55 percent and 85 percent.
Google also announced that web and mobile versions of Google Translate are now using a new neural machine translation system for all translations from Chinese into English. According to the company, the app conducts those translations about 18 million times a day. Translating from Chinese to English is one of the more than 10,000 language pairs supported by Google Translate, and the company plans to work on rolling out GNMT to many more of these over the coming months.
A few years ago we started using Recurrent Neural Networks (RNNs) to directly learn the mapping between an input sequence (e.g. a sentence in one language) to an output sequence (that same sentence in another language) . Whereas Phrase-Based Machine Translation (PBMT) breaks an input sentence into words and phrases to be translated largely independently, Neural Machine Translation (NMT) considers the entire input sentence as a unit for translation.The advantage of this approach is that it requires fewer engineering design choices than previous Phrase-Based translation systems. When it first came out, NMT showed equivalent accuracy with existing Phrase-Based translation systems on modest-sized public benchmark data sets.