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Discrete utterance recognition based on nonlinear model identification with single layer neural networks

  • Sam Kwong
  • , Gang Wei
  • , Yiu Keung Chan
  • , Jing Zheng Ouyang

    Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

    Abstract

    In this paper, a scheme for speaker independent discrete utterance recognition using single layer neural network (SLNN) based nonlinear auto regression model parameters as the features is presented. A fast training algorithm is developed for the identification of the model parameters. Dynamic programming is used for the pattern matching. The experimental results of speaker independent recognition of 10 digits are reported.
    Original languageEnglish
    Title of host publicationProceedings - IEEE International Symposium on Circuits and Systems
    PublisherIEEE
    Pages2419-2422
    Volume4
    ISBN (Print)780312813
    Publication statusPublished - 1993
    EventProceedings of the 1993 IEEE International Symposium on Circuits and Systems - Chicago, IL, USA
    Duration: 3 May 19936 May 1993

    Publication series

    Name
    Volume4
    ISSN (Electronic)0271-4310

    Conference

    ConferenceProceedings of the 1993 IEEE International Symposium on Circuits and Systems
    CityChicago, IL, USA
    Period3/05/936/05/93

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