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
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