Text-translation alignment

  • Authors:
  • Martin Kay;Martin Röscheisen

  • Affiliations:
  • Xerox Palo Alto Research Center and Stanford University;Xerox Palo Alto Research Center and Technical University of Munich

  • Venue:
  • Computational Linguistics - Special issue on using large corpora: I
  • Year:
  • 1993

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Abstract

We present an algorithm for aligning texts with their translations that is based only on internal evidence. The relaxation process rests on a notion of which word in one text corresponds to which word in the other text that is essentially based on the similarity of their distributions. It exploits a partial alignment of the word level to induce a maximum likelihood alignment of the sentence level, which is in turn used, in the next iteration, to refine the word level estimate. The algorithm appears to converge to the correct sentence alignment in only a few iterations.