• DocumentCode
    3315130
  • Title

    Mandarin Digital Speech Recognition Based on a Chaotic Neural Network and Fuzzy C-means Clustering

  • Author

    Li, Guang ; Zhang, Jin ; Freeman, Walter J.

  • Author_Institution
    Zhejiang Univ., Hangzhou
  • fYear
    2007
  • fDate
    23-26 July 2007
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Modeling olfactory neural systems, the Kill model proposed by Freeman exhibits chaotic dynamic characteristics and has potential for pattern recognition. Fuzzy c-means clustering can classify an object to several classes at the same time but with different degrees based on fuzzy sets theory. Based on the Kill model, mandarin digital speech is recognized utilizing the features extracted by the fuzzy c-means clustering. Experimental results show that the Kill model can perform digital speech recognition efficiently and the fuzzy c-means clustering has better performance than the hard k-means clustering.
  • Keywords
    feature extraction; fuzzy set theory; neural nets; pattern clustering; speech recognition; Kill model; Mandarin digital speech recognition; chaotic neural network; fuzzy c-means clustering; fuzzy sets theory; olfactory neural systems; pattern recognition; Chaos; Clustering algorithms; Data mining; Feature extraction; Fuzzy neural networks; Hidden Markov models; Neural networks; Olfactory; Pattern recognition; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International
  • Conference_Location
    London
  • ISSN
    1098-7584
  • Print_ISBN
    1-4244-1209-9
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZY.2007.4295337
  • Filename
    4295337