A Discriminative Syntactic Word Order Model for Machine Translation

@inproceedings{Chang2007ADS,
  title={A Discriminative Syntactic Word Order Model for Machine Translation},
  author={Pi-Chuan Chang and Kristina Toutanova},
  booktitle={ACL},
  year={2007}
}
We present a global discriminative statistical word order model for machine translation. Our model combines syntactic movement and surface movement information, and is discriminatively trained to choose among possible word orders. We show that combining discriminative training with features to detect these two different kinds of movement phenomena leads to substantial improvements in word ordering performance over strong baselines. Integrating this word order model in a baseline MT system… CONTINUE READING
Highly Cited
This paper has 40 citations. REVIEW CITATIONS

From This Paper

Figures, tables, results, and topics from this paper.

Key Quantitative Results

  • Integrating this word order model in a baseline MT system results in a 2.4 points improvement in BLEU for English to Japanese translation.

Citations

Publications citing this paper.
Showing 1-10 of 25 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 16 references

Similar Papers

Loading similar papers…