Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation

Google (United States)

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Abstract

We propose a simple solution to use a single Neural Machine Translation (NMT) model to translate between multiple languages. Our solution requires no changes to the model architecture from a standard NMT system but instead introduces an artificial token at the beginning of the input sentence to specify the required target language. Using a shared wordpiece vocabulary, our approach enables Multilingual NMT systems using a single model. On the WMT’14 benchmarks, a single multilingual model achieves comparable performance for English→French and surpasses state-of-theart results for English→German. Similarly, a single multilingual model surpasses state-of-the-art results for French→English and German→English on…

Citation impact

1,738
total citations
FWCI
175.85
Percentile
100%
References
31
Citations per year

Authors

12

Topics & keywords

Keywords
  • Computer science
  • Machine translation
  • Natural language processing
  • Artificial intelligence
  • Sentence
  • Language model
  • German
  • Security token
UN Sustainable Development Goals
  • Quality Education
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