• DocumentCode
    3481715
  • Title

    Speeh/music classification by using statistical neural networks

  • Author

    Bolat, Bülent ; Küçük, Üna1

  • Author_Institution
    Yildiz Teknik Universitesi, Istanbul, Turkey
  • fYear
    2004
  • fDate
    28-30 April 2004
  • Firstpage
    227
  • Lastpage
    229
  • Abstract
    This paper represents a framework for speech/music classification by using statistical neural networks. Zero crossing rate, root mean square power and spectral centroid were used as features. A dataset including 150 audio instances was labeled manually and 105 of them were used to train different networks, which are the probabilistic neural network (PNN), the generalised regression neural network (GRNN) and the radial basis functions (RBF). The remainder of the dataset was used as test item. Training and test performance of these three network types were discussed.
  • Keywords
    learning (artificial intelligence); music; radial basis function networks; regression analysis; signal classification; spectral analysis; speech processing; GRNN; PNN; RBF; generalised regression neural network; neural network training; probabilistic neural network; radial basis functions; root mean square power; spectral centroid; speech/music classification; statistical neural networks; zero crossing rate; Cepstral analysis; Discrete Fourier transforms; Gaussian processes; Multiple signal classification; Neural networks; Performance evaluation; Root mean square; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference, 2004. Proceedings of the IEEE 12th
  • Print_ISBN
    0-7803-8318-4
  • Type

    conf

  • DOI
    10.1109/SIU.2004.1338300
  • Filename
    1338300