Most studies find that neural machine-translation models can translate only about 30 percent of novel excerpts—usually simple passages—with acceptable quality, as determined by native speakers.

For language translation tasks, traditional machine translation systems like Google Translate and those based on Statistical Machine Translation (SMT) or Neural Machine Translation (NMT) have been ...

Discover five powerful AI tools for translation that leverage machine learning and natural language processing techniques.

Statistical machine translation has seen significant improvements in quality over the past several years. The single biggest factor in this improvement has been the accumulation of ever larger stores ...

The translation features typically used in Phrase-Based Statistical Machine Translation (PB-SMT) model dependencies between the source and target phrases, but not among the phrases in the source ...

Google Translate has been around since April 2006, evolving from a basic statistical machine translation tool into a neural machine translation system supporting over 130 languages and billions of ...

Google, Microsoft and Facebook have been making the move to neural machine translation for some time now, rapidly leaving old-school phrase-based statistical machine translation behind.

Google's approach, called statistical machine translation, differs from past efforts in that it forgoes language experts who program grammatical rules and dictionaries into computers.