Weighted Finite-State Transducer Inference for Limited-Domain Speech-to-Speech Translation

  • Diamantino Caseiro
  • Isabel Trancoso
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3960)


A speech input machine translation system based on weighted finite state transducers is presented. This system allows for a tight integration of the speech recognition with the machine translation modules. Transducer inference algorithms to automatically learn the translation module are also presented. Good experimental results confirmed the adequacy of these techniques to limited-domain tasks. In particular, the reordering algorithm proposed showed impressive improvements by reducing the error rate in excess of 50%.


Speech Recognition Machine Translation Automatic Speech Recognition Translation Model 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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  1. 1.
    Mohri, M., Pereira, F., Riley, M.: Weighted finite-state transducers in speech recognition. In: ASR 2000 Workshop, Paris, France (2000)Google Scholar
  2. 2.
    Hetherington, I.: An efficient implementation of phonological rules using finitestate transducers. In: Proc. Eurospeech 2001, Aalborg, Denmark (2001)Google Scholar
  3. 3.
    Knight, K., Al-Onaizan, Y.: Translation with finite-state devices. In: Farwell, D., Gerber, L., Hovy, E. (eds.) AMTA 1998. LNCS (LNAI), vol. 1529, pp. 421–437. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  4. 4.
    Gale, W., Church, K.: A program for aligning sentences in bilingual corpora. Computational Linguistics 102, 19–75 (1993)Google Scholar
  5. 5.
    Bangalore, S., Riccardia, G.: Stochastic finite-state models for spoken language machine translation. In: Workshop on Embedded Machine Translation Systems, Seattle, EUA (2000)Google Scholar
  6. 6.
    Oncina, J., Castellanos, A., Vidal, E., Jimenez, V.: Corpus–based machine translation through subsequential transducers. In: Third International Conference on the Cognitive Science of Natural Language Processing, Dublin, Ireland (1994)Google Scholar
  7. 7.
    García-Varea, I., Sanchis, A., Casacuberta, F.: A new approach to speech-input statistical translation. In: 15th International Conference on Pattern Recognition, Barcelona, Spain, vol. 3, pp. 94–97. IEEE Computer Society, Los Alamitos (2000)Google Scholar
  8. 8.
    Casacuberta, F., Vidal, E., Picó, D.: Inference of finite-state transducers from regular languages. Pattern Recognition 38, 1431–1442 (2005)CrossRefGoogle Scholar
  9. 9.
    Meinedo, H., Caseiro, D., Neto, J., Trancoso, I.: Audimus. media: a broadcast news speech recognition system for the european portuguese language. In: Mamede, N.J., Baptista, J., Trancoso, I., Nunes, M.d.G.V. (eds.) PROPOR 2003. LNCS, vol. 2721, pp. 9–17. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  10. 10.
    Caseiro, D.: Finite-State Methods in Automatic Speech Recognition. PhD thesis, Instituto Superior Técnico, Universidade Técnica de Lisboa (2003)Google Scholar
  11. 11.
    Och, F.J., Ney, H.: A systematic comparison of various statistical alignment models. Computational Linguistics 29, 19–51 (2003)CrossRefGoogle Scholar
  12. 12.
    Casacuberta, F.: Inference of finite-state transducers by using regular grammars and morphisms. In: Oliveira, A.L. (ed.) ICGI 2000. LNCS (LNAI), vol. 1891, pp. 1–14. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  13. 13.
    Riccardi, G., Bocchieri, E., Pieraccini, R.: Non deterministic stochastic language models for speech recognition. In: Proc. ICASSP 1995, Detroit, USA, pp. 237–240 (1995)Google Scholar
  14. 14.
    Stolcke, A.: Srilm - an extensible language modeling toolkit. In: Proc. ICSLP 2002, Denver, Colorado, USA (2002)Google Scholar
  15. 15.
    Amengual, J., Benedí, J., Casacuberta, F., Castaño, A., Castellanos, A., Jiménez, V., Llorens, D., Marzal, A., Pastor, M., Prat, F., Vidal, E., Vilar, J.: The eutrans-i speech translation system. Machine Translation 15, 75–103 (2000)CrossRefGoogle Scholar
  16. 16.
    Meinedo, H., Souto, N., Neto, J.: Speech recognition of broadcast news for the European portuguese language. In: Automatic Speech Recognition and Understanding ASRU 2001, Madona de Campilho, Trento, Italy (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Diamantino Caseiro
    • 1
  • Isabel Trancoso
    • 1
  1. 1.L2F INESC-ID/ISTPortugal

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