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OpenFst: A General and Efficient Weighted Finite-State Transducer Library

(Extended Abstract of an Invited Talk)
  • Cyril Allauzen
  • Michael Riley
  • Johan Schalkwyk
  • Wojciech Skut
  • Mehryar Mohri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4783)

Abstract

We describe OpenFst, an open-source library for weighted finite-state transducers (WFSTs). OpenFst consists of a C++ template library with efficient WFST representations and over twenty-five operations for constructing, combining, optimizing, and searching them. At the shell-command level, there are corresponding transducer file representations and programs that operate on them. OpenFst is designed to be both very efficient in time and space and to scale to very large problems.

This library has key applications speech, image, and natural language processing, pattern and string matching, and machine learning.

We give an overview of the library, examples of its use, details of its design that allow customizing the labels, states, and weights and the lazy evaluation of many of its operations.

Further information and a download of the OpenFst library can be obtained from http://www.openfst.org.

Keywords

weighted automata finite-state transducers rational power series 

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References

  1. 1.
    Mohri, M., Pereira, F., Riley, M.: The design principles of a weighted finite-state transducer library. Theoretical Computer Science 231, 17–32 (2000)zbMATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    Adant, A.: WFST: a finite-state template library in C++ (2000), http://membres.lycos.fr/adant/tfe
  3. 3.
    Hetherington, L.: The MIT finite-state transducer toolkit for speech and language processing. In: Proceedings of the ICSLP, Jeju, South Korea (2004)Google Scholar
  4. 4.
    Kanthak, S., Ney, H.: FSA: An efficient and flexible C++ toolkit for finite state automata using on-demand computation. In: Proceedings of 42nd Meeting of the ACL, pp. 510–517 (2004)Google Scholar
  5. 5.
    Lombardy, S., Régis-Gianas, Y., Sakarovitch, J.: Introducing VAUCANSON. Theoretical Computer Science 328, 77–96 (2004)zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Salomaa, A., Soittola, M.: Automata-Theoretic Aspects of Formal Power Series. Springer, New York (1978)zbMATHGoogle Scholar
  7. 7.
    Kuich, W., Salomaa, A.: Semirings, Automata, Languages. Number 5 in EATCS Monographs on Theoretical Computer Science. Springer, Germany (1986)zbMATHGoogle Scholar
  8. 8.
    Berstel, J., Reutenauer, C.: Rational Series and Their Languages. Springer, New York (1988)zbMATHGoogle Scholar
  9. 9.
    Cortes, C., Mohri, M., Rastogi, A., Riley, M.: On the computation of the relative entropy of probabilistic automata. International Journal of Foundations of Computer Science (2007)Google Scholar
  10. 10.
    Mohri, M.: Finite-state transducers in language and speech processing. Computational Linguistics 23 (1997)Google Scholar
  11. 11.
    Mohri, M.: Minimization algorithms for sequential transducers. Theoretical Computer Science 234, 177–201 (2000)zbMATHCrossRefMathSciNetGoogle Scholar
  12. 12.
    Mohri, M.: Generic epsilon-removal and input epsilon-normalization algorithms for weighted transducers. International Journal of Foundations of Computer Science 13, 29–143 (2002)CrossRefMathSciNetGoogle Scholar
  13. 13.
    Mohri, M.: Semiring frameworks and algorithms for shortest-distance problems. Journal of Automata, Languages and Combinatorics 7, 321–350 (2002)zbMATHMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Cyril Allauzen
    • 1
  • Michael Riley
    • 2
  • Johan Schalkwyk
    • 2
  • Wojciech Skut
    • 2
  • Mehryar Mohri
    • 1
  1. 1.Courant Institute of Mathematical Sciences, 251 Mercer ST, New York, NY 10012USA
  2. 2.Google, Inc., 111 Eighth AV, New York, NY 10011USA

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