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