• DocumentCode
    397074
  • Title

    Binding of audio elements in the sound source segregation problem via a two-layered bio-inspired neural network

  • Author

    Pichevar, Ramin ; Rouat, Jean

  • Author_Institution
    GEGI, Univ. de Sherbrooke, Que., Canada
  • Volume
    2
  • fYear
    2003
  • fDate
    4-7 May 2003
  • Firstpage
    1151
  • Abstract
    We use a two-layered bio-inspired neural network to segregate sound sources, i.e. double-vowels or intruding noises in speech. The architecture of the network consists of spiking neurons. The spiking neurons in both layers are modelized by relaxation oscillators. The first layer of the network is locally connected, while the second layer is a fully connected network. Our auditory image is based on the reassigned spectrum technique. No prior estimation or knowledge of pitch is necessary for the segregation.
  • Keywords
    neural nets; relaxation oscillators; speech processing; auditory image; cochleotopic-AMtopic maps; cocktail-party effect; computational auditory scene analysis; double-vowels; reassigned spectrum technique; relaxation oscillators; sound source segregation; two-layered bio-inspired neural network; Biological neural networks; Humans; Image analysis; Independent component analysis; Intelligent networks; Layout; Neural networks; Neurons; Psychology; Speech;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Computer Engineering, 2003. IEEE CCECE 2003. Canadian Conference on
  • ISSN
    0840-7789
  • Print_ISBN
    0-7803-7781-8
  • Type

    conf

  • DOI
    10.1109/CCECE.2003.1226101
  • Filename
    1226101