Can We Relearn an RBMT System?

Loïc Dugast, Jean Senellart, Philipp Koehn

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

Abstract

This paper describes SYSTRAN submissions for the shared task of the third Workshop on Statistical Machine Translation at ACL. Our main contribution consists in a French-English statistical model trained without the use of any human-translated parallel corpus. In substitution, we translated a monolingual corpus with SYSTRAN rule-based translation engine to produce the parallel corpus. The results are provided herein, along with a measure of error analysis.
Original languageEnglish
Title of host publicationProceedings of the Third Workshop on Statistical Machine Translation
Place of PublicationStroudsburg, PA, USA
PublisherAssociation for Computational Linguistics
Pages175-178
Number of pages4
Publication statusPublished - 2008

Fingerprint

Dive into the research topics of 'Can We Relearn an RBMT System?'. Together they form a unique fingerprint.

Cite this