• DocumentCode
    2721303
  • Title

    Learning vector quantization, multi layer perceptron and dynamic programming: comparison and cooperation

  • Author

    Driancourt, Xavier ; Bottou, Léon ; Gallinari, Patrick

  • Author_Institution
    LRI Univ. Paris Sud, Orsay, France
  • fYear
    1991
  • fDate
    8-14 Jul 1991
  • Firstpage
    815
  • Abstract
    The authors compare dynamic programming, or DP, multilayer perceptron, time-delay neural network, or TDNN, shift-tolerant learning vector quantization, and K-means on a multispeaker isolated-word small vocabulary problem. A suboptimal cooperation between TDNN and other algorithms is proposed and successfully tested on the problem. The combination of TDNN and DP performs especially well. An optimal cooperation method between DP and some other algorithms is proposed
  • Keywords
    delays; dynamic programming; learning systems; neural nets; speech recognition; K-means; learning; multilayer perceptron; multispeaker isolated-word small vocabulary problem; suboptimal cooperation; time-delay neural network; vector quantisation; Databases; Dynamic programming; Event detection; Hidden Markov models; Neural networks; Speech recognition; Stochastic processes; Testing; Vector quantization; Vocabulary;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7803-0164-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.1991.155439
  • Filename
    155439