Application of a modified neural fuzzy network and an improved genetic algorithm to speech recognition

被引：0
作者：
K. F. Leung
F. H. F. Leung
H. K. Lam
S. H. Ling
机构：
[1] The Hong Kong Polytechnic University,Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering
[2] King’s College London,Division of Engineering
来源：
Neural Computing and Applications | 2007年 / 16卷
关键词：
Neural network; Genetic algorithm; Fuzzy logic; Speech recognition; Pattern recognition;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
引用
收藏
页码：419 / 431
页数：12
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