Translating from complex to simplified sentences

  • Authors:
  • Lucia Specia

  • Affiliations:
  • Research Group in Computation Linguistics, University of Wolverhampton, Wolverhmapton, UK

  • Venue:
  • PROPOR'10 Proceedings of the 9th international conference on Computational Processing of the Portuguese Language
  • Year:
  • 2010

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Abstract

We address the problem of simplifying Portuguese texts at the sentence level by treating it as a “translation task”. We use the Statistical Machine Translation (SMT) framework to learn how to translate from complex to simplified sentences. Given a parallel corpus of original and simplified texts, aligned at the sentence level, we train a standard SMT system and evaluate the “translations” produced using both standard SMT metrics like BLEU and manual inspection. Results are promising according to both evaluations, showing that while the model is usually overcautious in producing simplifications, the overall quality of the sentences is not degraded and certain types of simplification operations, mainly lexical, are appropriately captured.