Source language categorization for improving a speech into sign language translation system

  • Authors:
  • V. López-Ludeña;R. San-Segundo;S. Lutfi;J. M. Lucas-Cuesta;J. D. Echevarry;B. Martínez-González

  • Affiliations:
  • Universidad Politécnica de Madrid;Universidad Politécnica de Madrid;Universidad Politécnica de Madrid;Universidad Politécnica de Madrid;Universidad Politécnica de Madrid;Universidad Politécnica de Madrid

  • Venue:
  • SLPAT '11 Proceedings of the Second Workshop on Speech and Language Processing for Assistive Technologies
  • Year:
  • 2011

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Abstract

This paper describes a categorization module for improving the performance of a Spanish into Spanish Sign Language (LSE) translation system. This categorization module replaces Spanish words with associated tags. When implementing this module, several alternatives for dealing with non-relevant words have been studied. Non-relevant words are Spanish words not relevant in the translation process. The categorization module has been incorporated into a phrase-based system and a Statistical Finite State Transducer (SFST). The evaluation results reveal that the BLEU has increased from 69.11% to 78.79% for the phrase-based system and from 69.84% to 75.59% for the SFST.