Inducing probabilistic invertible translation grammars from aligned texts

  • Authors:
  • Michael Carl

  • Affiliations:
  • Institut für Angewandte Informationsforschung, Saarbrücken, Germany

  • Venue:
  • ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
  • Year:
  • 2001

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Abstract

This paper presents an algorithm for extracting invertible probabilistic translation grammars from bilingual aligned and linguistically bracketed text. The invertibility condition requires all translation ambiguities to be resolved in the final translation grammar. The paper examines the complexity of inducing translation grammars and proposes a number of heuristics to reduce the the theoretically exponential computation time.