A Maximum Entropy Approach to Syntactic Translation Rule Filtering

Marcin Junczys-Dowmunt

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this paper we will present a maximum entropy filter for the translation rules of a statistical machine translation system based on tree transducers. This filter can be successfully used to reduce the number of translation rules by more than 70% without negatively affecting translation quality as measured by BLEU. For some filter configurations, translation quality is even improved.
Our investigations include a discussion of the relationship of Alignment Error Rate and Consistent Translation Rule Score with translation quality in the context of Syntactic Statistical Machine Translation.
Original languageEnglish
Title of host publicationComputational Linguistics and Intelligent Text Processing
Subtitle of host publication11th International Conference, CICLing 2010, Iai, Romania, March 21-27, 2010. Proceedings
EditorsAlexander Gelbukh
Place of PublicationBerlin, Heidelberg
PublisherSpringer Berlin Heidelberg
Pages451-463
Number of pages13
ISBN (Electronic)978-3-642-12116-6
ISBN (Print)978-3-642-12115-9
DOIs
Publication statusPublished - 2010

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
Volume6008
ISSN (Print)0302-9743

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