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.
Original language | English |
---|---|
Pages (from-to) | 419-431 |
Number of pages | 13 |
Journal | Neural Computing and Applications |
Volume | 16 |
Issue number | 4-5 |
DOIs | |
Publication status | Published - 1 May 2007 |
Keywords
- Fuzzy logic
- Genetic algorithm
- Neural network
- Pattern recognition
- Speech recognition
ASJC Scopus subject areas
- Control and Systems Engineering
- Artificial Intelligence