Title
Application of a modified neural fuzzy network and an improved genetic algorithm to speech recognition
Abstract
This paper presents the recognition of speech commands using a modified neural fuzzy network (NFN). By introducing associative memory (the tuner NFN) into the classification process (the classifier NFN), the network parameters could be made adaptive to changing input data. Then, the search space of the classification network could be enlarged by a single network. To train the parameters of the modified NFN, an improved genetic algorithm is proposed. As an application example, the proposed speech recognition approach is implemented in an eBook experimentally to illustrate the design and its merits.
Year
DOI
Venue
2007
10.1007/s00521-006-0068-4
Neural Computing and Applications
Keywords
DocType
Volume
modified neural fuzzy network,tuner NFN,network parameter,classification network,neural network æ genetic algorithm æ fuzzy logic æ speech recognition æ pattern recognition,proposed speech recognition approach,classifier NFN,classification process,single network,modified NFN,improved genetic algorithm,application example
Journal
16
Issue
ISSN
Citations 
4
1433-3058
14
PageRank 
References 
Authors
0.61
7
4
Name
Order
Citations
PageRank
K. F. Leung1311.84
F. H. F. Leung2484.80
H. K. Lam33618193.15
S. H. Ling460940.29