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

Publisher:
Springer
Publication Type:
Journal Article
Citation:
Neural Computing & Applications, 2007, 16 (4-5), pp. 419 - 431
Issue Date:
2007-01
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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.
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