Title :
Neural fuzzy network and genetic algorithm approach for Cantonese speech command recognition
Author :
Leung, K.F. ; Leung, F.H.F. ; Lam, H.K. ; Tam, P.K.S.
Author_Institution :
Centre for Multimedia Signal Process., Hong Kong Polytech. Univ., Kowloon, China
Abstract :
This paper presents the recognition of Cantonese speech commands using a proposed neural fuzzy network with rule switches. By introducing a switch to each rule, the optimal number of rules can be learned. An improved genetic algorithm (GA) is proposed to train the parameters of the membership functions and the optimal rule set for the proposed neural fuzzy network. An application example of Cantonese command recognition in electronic books will be given to illustrate the merits of the proposed approach.
Keywords :
electronic publishing; feature extraction; fuzzy neural nets; genetic algorithms; learning (artificial intelligence); speech recognition; Cantonese speech command recognition; crossover operation; directed random search; electronic books; improved genetic algorithm; learning algorithm; membership functions; neural fuzzy network; optimal number of rules; rule switches; speech classification; Artificial neural networks; Feature extraction; Filter bank; Fuzzy neural networks; Genetic algorithms; Hidden Markov models; Linear predictive coding; Speech processing; Speech recognition; Switches;
Conference_Titel :
Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
Print_ISBN :
0-7803-7810-5
DOI :
10.1109/FUZZ.2003.1209363