• DocumentCode
    2706220
  • Title

    Modeling melody recognition using a sequence recognition neural network with meta-level processes

  • Author

    Vempala, Naresh N. ; Maida, Anthony S.

  • Author_Institution
    Inst. of Cognitive Sci., Univ. of Louisiana at Lafayette, Lafayette, LA, USA
  • fYear
    2009
  • fDate
    14-19 June 2009
  • Firstpage
    3204
  • Lastpage
    3211
  • Abstract
    This research models human performance in the Dalla Bella, Peretz, and Aronoff melody recognition study. They compared performance between musicians and nonmusicians in the recognition (and perception) of melodies. They used a gating task to identify three events in the melody perception/recognition process. These were the familiarity emergence point (FEP), the isolation point (IP), and the recognition point (RP). We develop a simulation to model hypothesized cognitive processes underlying these events. The IP is modeled using a winner-take-all connectionist network adapted to operate with temporal input sequences. Meta-level processes examine the dynamic state of the recognition network to model the FEP and the RP.
  • Keywords
    audio signal processing; music; neural nets; Aronoff melody recognition study; familiarity emergence point; human performance; hypothesized cognitive processes; isolation point; melody perception; metalevel processes; nonmusicians; recognition network; recognition point; sequence recognition neural network; winner-take-all connectionist network; Cognitive science; Discrete event simulation; Hopfield neural networks; Humans; Lesions; Monitoring; Neural networks; Psychology; Rhythm; Vocabulary;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2009. IJCNN 2009. International Joint Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-3548-7
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2009.5178610
  • Filename
    5178610