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Finite State Transducers Based on k-TSS Grammars for Speech Translation

  • A. Pérez
  • F. Casacuberta
  • I. Torres
  • V. Guijarrubia
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4002)

Abstract

Finite state transducers can be automatically learnt from bilingual corpus, and they can be easily integrated in an automatic speech recognition system for speech translation applications. In this work we explore the possibility of using k-testable language models to generate translations models. We report speech translation results for one easy and well known task, EuTrans (Spanish-English), and for other similar task, Euskal Turista (Spanish-Basque). Euskal Turista has proved to be a quite difficult task because of the distance between the languages involved.

Keywords

Machine Translation Speech Recognition System Statistical Machine Translation Word Error Rate Automatic Speech Recognition System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    Casacuberta, F., Vidal, E.: Machine translation with inferred stochastic finite-state transducers. Computational Linguistics 30, 205–225 (2004)MathSciNetCrossRefMATHGoogle Scholar
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    Torres, I., Varona, A.: k-tss language models in a speech recognition systems. Computer Speech and Language 15, 127–149 (2001)CrossRefGoogle Scholar
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    Amengual, J., Benedí, J., Casacuberta, F., Castaño, M., Castellanos, A., Jiménez, V., Llorens, D., Marzal, A., Pastor, M., Prat, F., Vidal, E., Vilar, J.: The EuTrans-I speech translation system. Machine Translation 1 (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • A. Pérez
    • 1
  • F. Casacuberta
    • 2
  • I. Torres
    • 1
  • V. Guijarrubia
    • 1
  1. 1.Universidad del País VascoSpain
  2. 2.Universidad Politécnica de ValenciaSpain

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