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arxiv: 1804.08198 · v3 · pith:JEWDFJB3new · submitted 2018-04-23 · 💻 cs.CL

A neural interlingua for multilingual machine translation

classification 💻 cs.CL
keywords neuraltranslationinterlinguamachinemultilingualapproacharchitecturebilingual
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We incorporate an explicit neural interlingua into a multilingual encoder-decoder neural machine translation (NMT) architecture. We demonstrate that our model learns a language-independent representation by performing direct zero-shot translation (without using pivot translation), and by using the source sentence embeddings to create an English Yelp review classifier that, through the mediation of the neural interlingua, can also classify French and German reviews. Furthermore, we show that, despite using a smaller number of parameters than a pairwise collection of bilingual NMT models, our approach produces comparable BLEU scores for each language pair in WMT15.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges

    cs.CL 2019-07 unverdicted novelty 5.0

    A single multilingual NMT model for 103 languages trained on 25B examples demonstrates transfer learning benefits for low-resource languages.