Can We Relearn an RBMT System?

Loïc Dugast; Jean Senellart; Philipp Koehn

Can We Relearn an RBMT System?

Loïc Dugast, Jean Senellart, Philipp Koehn

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Proceedings of the Third Workshop on Statistical Machine Translation
Place of Publication	Stroudsburg, PA, USA
Publisher	Association for Computational Linguistics
Pages	175-178
Number of pages	4
Publication status	Published - 2008

Access to Document

http://dl.acm.org/citation.cfm?id=1626394.1626421

Cite this

@inproceedings{7e7e6c2c14324b2197cd983da88f9402,

title = "Can We Relearn an RBMT System?",

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.",

author = "Lo{\"i}c Dugast and Jean Senellart and Philipp Koehn",

year = "2008",

language = "English",

pages = "175--178",

booktitle = "Proceedings of the Third Workshop on Statistical Machine Translation",