Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/18016
Title: Application of a modified neural fuzzy network and an improved genetic algorithm to speech recognition
Authors: Leung, KF
Leung, FHF 
Lam, HK
Ling, SH
Keywords: Fuzzy logic
Genetic algorithm
Neural network
Pattern recognition
Speech recognition
Issue Date: 2007
Publisher: Springer
Source: Neural computing and applications, 2007, v. 16, no. 4-5, p. 419-431 How to cite?
Journal: Neural Computing and Applications 
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.
URI: http://hdl.handle.net/10397/18016
DOI: 10.1007/s00521-006-0068-4
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