Article thumbnail
Location of Repository

Computational Linguistics

By Jakob Elming

Abstract

We present a novel approach to word re-ordering which successfully integrates syn-tactic structural knowledge with phrase-based SMT. This is done by constructing a lattice of alternatives based on automatically learned probabilistic syntactic rules. In decoding, the alternatives are scored based on the output word order, not the order of the input. Un-like previous approaches, this makes it possi-ble to successfully integrate syntactic reorder-ing with phrase-based SMT. On an English-Danish task, we achieve an absolute improve-ment in translation quality of 1.1 % BLEU. Manual evaluation supports the claim that the present approach is significantly superior to previous approaches.

Year: 2014
OAI identifier: oai:CiteSeerX.psu:10.1.1.488.9879
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://www.mt-archive.info/ACL... (external link)
  • http://www.mt-archive.info/ACL... (external link)
  • http://citeseerx.ist.psu.edu/v... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.