DocumentCode
2743874
Title
Speech classification using a modified focused gamma network
Author
Kuo, Jyh-Ming ; Ipe, Jose C Princ
Author_Institution
Dept. of Electron. Eng., Kaohsiung Polytech. Inst., Taiwan
Volume
4
fYear
1996
fDate
3-6 Jun 1996
Firstpage
1877
Abstract
A modified version of the focused gamma network is proposed and applied to speech classification. Each input neuron of the network is equipped with a pair of gamma memories which have an adjustable time-scale parameter. In addition, each channel of speech features is equally divided into several segments, and each segment is clocked into an individual input neuron. With these modifications, the network is able to develop a proper time scale for each segment of patterns and handle speech patterns of different lengths as well
Keywords
filtering theory; multilayer perceptrons; network topology; pattern classification; speech recognition; focused gamma network; gamma filter; gamma memory; input neuron; multilayer perceptron; network topology; neural networks; speech classification; speech recognition; time-scale parameter; Clocks; Convergence; Delay lines; Filters; Multilayer perceptrons; Neural networks; Neurons; Speech processing; Speech recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1996., IEEE International Conference on
Conference_Location
Washington, DC
Print_ISBN
0-7803-3210-5
Type
conf
DOI
10.1109/ICNN.1996.549187
Filename
549187
Link To Document