Topological Ordering of Function Words in Hierarchical Phrase-based Translation

Hierarchical phrase-based models are attractive because they provide a consistent framework within which to characterize both local and long-distance reorderings, but they also make it difficult to distinguish many implausible reorderings from those that are linguistically plausible. Rather than appealing to annotation-driven syntactic modeling, we address this problem by observing the influential role of function words in determining syntactic structure, and introducing soft constraints on function word relationships as part of a standard log-linear hierarchical phrase-based model. Experimentation on Chinese-English and Arabic-English translation demonstrates that the approach yields significant gains in performance.

[1]  Philip Resnik,et al.  Online Large-Margin Training of Syntactic and Structural Translation Features , 2008, EMNLP.

[2]  Andreas Zollmann,et al.  Syntax Augmented Machine Translation via Chart Parsing , 2006, WMT@HLT-NAACL.

[3]  Bowen Zhou,et al.  Prior Derivation Models For Formally Syntax-Based Translation Using Linguistically Syntactic Parsing and Tree Kernels , 2008, SSST@ACL.

[4]  Haizhou Li,et al.  Ordering Phrases with Function Words , 2007, ACL.

[5]  Philipp Koehn,et al.  Statistical Significance Tests for Machine Translation Evaluation , 2004, EMNLP.

[6]  David Chiang,et al.  A Hierarchical Phrase-Based Model for Statistical Machine Translation , 2005, ACL.

[7]  Daniel Marcu,et al.  Statistical Phrase-Based Translation , 2003, NAACL.

[8]  Hermann Ney,et al.  Analysing soft syntax features and heuristics for hierarchical phrase based machine translation. , 2008, IWSLT.

[9]  David Chiang,et al.  Hierarchical Phrase-Based Translation , 2007, CL.

[10]  Hermann Ney,et al.  The Alignment Template Approach to Statistical Machine Translation , 2004, CL.

[11]  Dekai Wu,et al.  Stochastic Inversion Transduction Grammars and Bilingual Parsing of Parallel Corpora , 1997, CL.

[12]  Zhao Tie.  Increasing Accuracy of Chinese Segmentation with Strategy of Multi step Processing , 2001 .

[13]  Jinxi Xu,et al.  A New String-to-Dependency Machine Translation Algorithm with a Target Dependency Language Model , 2008, ACL.

[14]  Hermann Ney,et al.  Discriminative Training and Maximum Entropy Models for Statistical Machine Translation , 2002, ACL.

[15]  Hermann Ney,et al.  Improved backing-off for M-gram language modeling , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[16]  Philip Resnik,et al.  Soft Syntactic Constraints for Hierarchical Phrased-Based Translation , 2008, ACL.

[17]  Salim Roukos,et al.  Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.

[18]  William J. Byrne,et al.  Rule Filtering by Pattern for Efficient Hierarchical Translation , 2009, EACL.