Handling phrase reordering for machine translation

Y Ni, Saunders C., Szedmak S., Niranjan M.

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

9 Citations (Scopus)

Abstract

We propose a distance phrase reordering model (DPR) for statistical machine translation (SMT), where the aim is to capture phrase reorderings using a structure learning framework. On both the reordering classification and a Chinese-to-English translation task, we show improved performance over a baseline SMT system.
Translated title of the contributionHandling phrase reordering for machine translation
Original languageEnglish
Title of host publicationthe joint conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Singapore
Pages241 - 244
Number of pages4
Publication statusPublished - 2009

Bibliographical note

Conference Organiser: Association for Computational Linguistics (ACL)

Cite this