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
Link To Document :
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