Machine Translation

, 25:87

Deep open-source machine translation

  • Francis Bond
  • Stephan Oepen
  • Eric Nichols
  • Dan Flickinger
  • Erik Velldal
  • Petter Haugereid
Article

Abstract

This paper summarizes ongoing efforts to provide software infrastructure (and methodology) for open-source machine translation that combines a deep semantic transfer approach with advanced stochastic models. The resulting infrastructure combines precise grammars for parsing and generation, a semantic-transfer based translation engine and stochastic controllers. We provide both a qualitative and quantitative experience report from instantiating our general architecture for Japanese–English MT using only open-source components, including HPSG-based grammars of English and Japanese.

Keywords

Machine translation Open source Semantic transfer HPSG MRS 

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Francis Bond
    • 1
  • Stephan Oepen
    • 2
  • Eric Nichols
    • 3
  • Dan Flickinger
    • 4
  • Erik Velldal
    • 2
  • Petter Haugereid
    • 1
  1. 1.Division of Linguistics and Multilingual StudiesNanyang Technological UniversitySingaporeSingapore
  2. 2.Department of InformaticsUniversity of OsloOsloNorway
  3. 3.Graduate School of Information SciencesTohoku UniversitySendaiJapan
  4. 4.Center for the Study of Language and InformationStanford UniversityStanfordUSA

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