Inner-outer bracket models for word alignment using hidden blocks

  • Authors:
  • Bing Zhao;Niyu Ge;Kishore Papineni

  • Affiliations:
  • Carnegie Mellon University;IBM T. J. Watson Research Center, NY;IBM T. J. Watson Research Center, NY

  • Venue:
  • HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
  • Year:
  • 2005

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Abstract

Most statistical translation systems are based on phrase translation pairs, or "blocks", which are obtained mainly from word alignment. We use blocks to infer better word alignment and improved word alignment which, in turn, leads to better inference of blocks. We propose two new probabilistic models based on the inner-outer segmentations and use EM algorithms for estimating the models' parameters. The first model recovers IBM Model-1 as a special case. Both models outperform bidirectional IBM Model-4 in terms of word alignment accuracy by 10% absolute on the F-measure. Using blocks obtained from the models in actual translation systems yields statistically significant improvements in Chinese-English SMT evaluation.