• DocumentCode
    3233606
  • Title

    An associative memory approach to isolated-utterance speech recognition

  • Author

    Ervin, Thomas C., II ; Kim, Jung H.

  • Author_Institution
    Dept. of Electr. Eng., North Carolina A&T State Univ., Greensboro, NC, USA
  • fYear
    1993
  • fDate
    7-9 Mar 1993
  • Firstpage
    537
  • Lastpage
    539
  • Abstract
    A method for achieving isolated-utterance speech recognition using an associative recall algorithm is presented. The feature analysis methods used, as well as the implementation of the associative memory scheme, are highlighted. Preliminary experimental results have proved this method to be quite robust in the recognition aspect. Most of the experiments were performed with speaker-dependent tests and proved to be quite successful with a very limited vocabulary
  • Keywords
    Hopfield neural nets; content-addressable storage; convergence; correlation methods; learning by example; linear predictive coding; self-organising feature maps; speech recognition; associative memory scheme; associative recall algorithm; feature analysis; isolated-utterance speech recognition; speaker-dependent tests; Associative memory; Autocorrelation; Delay estimation; Linear predictive coding; Neural networks; Signal analysis; Spectral analysis; Speech analysis; Speech processing; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Theory, 1993. Proceedings SSST '93., Twenty-Fifth Southeastern Symposium on
  • Conference_Location
    Tuscaloosa, AL
  • ISSN
    0094-2898
  • Print_ISBN
    0-8186-3560-6
  • Type

    conf

  • DOI
    10.1109/SSST.1993.522838
  • Filename
    522838