Paper: A Direct Syntax-Driven Reordering Model for Phrase-Based Machine Translation

ACL ID N10-1127
Title A Direct Syntax-Driven Reordering Model for Phrase-Based Machine Translation
Venue Human Language Technologies
Session Main Conference
Year 2010
Authors

This paper presents a direct word reordering model with novel syntax-based features for sta- tistical machine translation. Reordering models address the problem of reordering source lan- guage into the word order of the target language. IBM Models 3 through 5 have reordering com- ponents that use surface word information but very little context information to determine the traversal order of the source sentence. Since the late 1990s, phrase-based machine translation solves much of the local reorderings by using phrasal translations. The problem of long- distance reordering has become a central re- search topic in modeling distortions. We present a syntax driven maximum entropy reordering model that directly predicts the source traversal order and is able to model arbitrar...