DocumentCode :
2744865
Title :
Isolated spoken number recognition with hybrid of self-organizing map and multilayer perceptron
Author :
Salmela, Petri ; Laurila, Kari ; Kuusisto, Seppo ; Haavisto, Petri ; Saarinen, Jukka
Author_Institution :
Electron. Lab., Tampere Univ. of Technol., Finland
Volume :
4
fYear :
1996
fDate :
3-6 Jun 1996
Firstpage :
1912
Abstract :
A neural network, which is capable of recognizing isolated spoken numbers speaker independently is described. The recognition system is a hybrid of a self-organizing map (SOM) and a multilayer perceptron (MLP). The SOM maps the feature vectors of a word in a constant dimension binary matrix, which is classified by a MLP. The decision borders of the SOM were fine-tuned with the LVQ1 algorithm, with which the hybrid achieved over 99% recognition out of 1232 test set samples. The training convergence of the MLP was tested with two different initialization methods
Keywords :
convergence; learning (artificial intelligence); multilayer perceptrons; self-organising feature maps; speech recognition; vector quantisation; LVQ1 algorithm; constant dimension binary matrix; decision borders; hybrid self-organizing map/multilayer perceptron; initialization methods; isolated spoken number recognition; training convergence; Commercialization; Isolation technology; Laboratories; Linear discriminant analysis; Mood; Multilayer perceptrons; Neural networks; Neurons; Speech recognition; Testing;
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.1996.549193
Filename :
549193
Link To Document :
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