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Large vocabulary speech recognition using neural-fuzzy and concept networks

  • Part III Speech Processing
  • Conference paper
  • First Online:
Neural Networks (EURASIP 1990)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 412))

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Abstract

This paper describes a new algorithm for large vocabulary speech recognition using two kinds of connectionist models. The first one is a phoneme recognition model which uses a method combining Neural Nets and Fuzzy Inference (here called Neural-Fuzzy). The other is a connected-word sequence selection method using semantic information about conceptual relationships among vocabulary words.

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References

  1. A. Amano, T. Aritsuka, N. Hataoka, and A. Ichikawa, On the Use of Neural Networks and Fuzzy Logic in Speech Recognition, in Proceedings of the IJCNN-89, June 1989

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  3. A. Amano, N. Hataoka, and A. Ichikawa, Phoneme Recognition Based On Phoneme-Pair Discrimination Rules, in Proceedings of 7th FASE Symposium, pp999, August 1988

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Author information

Authors and Affiliations

  1. Hitachi Dublin Laboratory, Trinity College, Dublin 2, Ireland

    Nobuo Hataoka

  2. Central Research Laboratory, Hitachi, Ltd., 185, Kokubunji, Tokyo, Japan

    Akio Amano, Toshiyuki Aritsuka & Akira Ichikawa

Authors
  1. Nobuo Hataoka
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  2. Akio Amano
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  3. Toshiyuki Aritsuka
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  4. Akira Ichikawa
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Editor information

Luis B. Almeida Christian J. Wellekens

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© 1990 Springer-Verlag Berlin Heidelberg

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Hataoka, N., Amano, A., Aritsuka, T., Ichikawa, A. (1990). Large vocabulary speech recognition using neural-fuzzy and concept networks. In: Almeida, L.B., Wellekens, C.J. (eds) Neural Networks. EURASIP 1990. Lecture Notes in Computer Science, vol 412. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-52255-7_39

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  • DOI: https://doi.org/10.1007/3-540-52255-7_39

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-52255-3

  • Online ISBN: 978-3-540-46939-1

  • eBook Packages: Springer Book Archive

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