Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions

Marcin Junczys-Dowmunt, Tomasz Dwojak, Hieu Hoang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we provide the largest published comparison of translation quality for phrase-based SMT and neural machine translation across 30 translation directions. For ten directions we also include hierarchical phrase-based MT. Experiments are performed for the recently published United Nations Parallel Corpus v1.0 and its large six-way sentence-aligned subcorpus. In the second part of the paper we investigate aspects of translation speed, introducing AmuNMT, our efficient neural machine translation decoder. We demonstrate that current neural machine translation could already be used for in-production systems when comparing words-per-second ratios.
Original languageEnglish
Title of host publicationProceedings of the International Workshop on Spoken Language Translation 2016
Place of PublicationJapan
Number of pages8
Volume1
Edition1
Publication statusPublished - 14 Dec 2016
Event13th International Workshop on Spoken Language Translation 2016 - Seattle, United States
Duration: 8 Dec 20169 Dec 2016
https://workshop2016.iwslt.org/

Conference

Conference13th International Workshop on Spoken Language Translation 2016
Abbreviated titleIWSLT 2016
Country/TerritoryUnited States
CitySeattle
Period8/12/169/12/16
Internet address

Keywords

  • Machine translation
  • Neural machine translation

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