• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations | Disambiguate

DMCA

Discriminative Training and Maximum Entropy Models for Statistical Machine Translation (2002)

Cached

  • Download as a PDF

Download Links

  • [www-i6.informatik.rwth-aachen.de]
  • [acl.ldc.upenn.edu]
  • [www.aclweb.org]
  • [www.aclweb.org]
  • [www.mt-archive.info]
  • [www.aclweb.org]
  • [acl.ldc.upenn.edu]
  • [aclweb.org]
  • [wing.comp.nus.edu.sg]
  • [aclweb.org]
  • [ucrel.lancs.ac.uk]
  • [aclweb.org]
  • [www.aclweb.org]
  • [wing.comp.nus.edu.sg]
  • [www.cs.toronto.edu]
  • [www.cs.utoronto.ca]
  • [www-rohan.sdsu.edu]
  • [www-i6.informatik.rwth-aachen.de]

  • Other Repositories/Bibliography

  • DBLP
  • Save to List
  • Add to Collection
  • Correct Errors
  • Monitor Changes
by Franz Josef Och , Hermann Ney
Citations:508 - 30 self
  • Summary
  • Citations
  • Active Bibliography
  • Co-citation
  • Clustered Documents
  • Version History

BibTeX

@INPROCEEDINGS{Och02discriminativetraining,
    author = {Franz Josef Och and Hermann Ney},
    title = {Discriminative Training and Maximum Entropy Models for Statistical Machine Translation},
    booktitle = {},
    year = {2002},
    pages = {295--302}
}

Share

Facebook Twitter Reddit Bibsonomy

OpenURL

 

Abstract

We present a framework for statistical machine translation of natural languages based on direct maximum entropy models, which contains the widely used source -channel approach as a special case. All knowledge sources are treated as feature functions, which depend on the source language sentence, the target language sentence and possible hidden variables.

Keyphrases

statistical machine translation    discriminative training    maximum entropy model    direct maximum entropy model    target language sentence    knowledge source    source language sentence    possible hidden variable    source channel approach    feature function    special case    natural language   

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University