Robustness beyond shallowness: incremental deep parsing
Natural Language Engineering
A syntax-based statistical translation model
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Dependency treelet translation: syntactically informed phrasal SMT
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Translating with non-contiguous phrases
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Hierarchical Phrase-Based Translation
Computational Linguistics
SPMT: statistical machine translation with syntactified target language phrases
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
A discriminative model for tree-to-tree translation
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
| Hi-index | 0.00 |
We describe experiments on discriminating English to French phrase-based translations through the use of syntactic "coupling" features. Using a robust rule-based dependency parser, we parse both the English source and the French translation candidates from the nbest list returned by our phrase-based system; we compute for each candidate a number of coupling features, that is, values that depend on the amount of alignment between edges in the source and target structures, and discriminatively train the weights of these coupling features. We compare different feature combinations. Although the improvements in terms of automatic measures such as Bleu and Nist are inconclusive, an initial human assessment of the results appears to show certain qualitative improvements.