• DocumentCode
    2709402
  • Title

    Using polynomial networks for speech recognition

  • Author

    Campbell, W.M. ; Broun, C.C.

  • Author_Institution
    Human Interface Lab., Motorola Inc., Tempe, AZ, USA
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    795
  • Abstract
    We consider the problem of using polynomial networks for speech recognition. Previous applications of polynomials to speech recognition have yielded systems which are difficult to train and have only moderate accuracy. We show that through a novel training algorithm, a probabilistic interpretation, and a novel scoring method, polynomial networks can be applied to speech recognition in a manner that is accurate and straightforward
  • Keywords
    hidden Markov models; learning (artificial intelligence); neural nets; probability; speech recognition; hidden Markov model; neural network; polynomial networks; probabilistic interpretation; scoring method; speech recognition; training algorithm; Artificial neural networks; Classification tree analysis; Databases; Hidden Markov models; Humans; Karhunen-Loeve transforms; Neural networks; Polynomials; Speech recognition; Viterbi algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks for Signal Processing X, 2000. Proceedings of the 2000 IEEE Signal Processing Society Workshop
  • Conference_Location
    Sydney, NSW
  • ISSN
    1089-3555
  • Print_ISBN
    0-7803-6278-0
  • Type

    conf

  • DOI
    10.1109/NNSP.2000.890159
  • Filename
    890159
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2709402