DocumentCode :
3315130
Title :
Mandarin Digital Speech Recognition Based on a Chaotic Neural Network and Fuzzy C-means Clustering
Author :
Li, Guang ; Zhang, Jin ; Freeman, Walter J.
Author_Institution :
Zhejiang Univ., Hangzhou
fYear :
2007
fDate :
23-26 July 2007
Firstpage :
1
Lastpage :
5
Abstract :
Modeling olfactory neural systems, the Kill model proposed by Freeman exhibits chaotic dynamic characteristics and has potential for pattern recognition. Fuzzy c-means clustering can classify an object to several classes at the same time but with different degrees based on fuzzy sets theory. Based on the Kill model, mandarin digital speech is recognized utilizing the features extracted by the fuzzy c-means clustering. Experimental results show that the Kill model can perform digital speech recognition efficiently and the fuzzy c-means clustering has better performance than the hard k-means clustering.
Keywords :
feature extraction; fuzzy set theory; neural nets; pattern clustering; speech recognition; Kill model; Mandarin digital speech recognition; chaotic neural network; fuzzy c-means clustering; fuzzy sets theory; olfactory neural systems; pattern recognition; Chaos; Clustering algorithms; Data mining; Feature extraction; Fuzzy neural networks; Hidden Markov models; Neural networks; Olfactory; Pattern recognition; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International
Conference_Location :
London
ISSN :
1098-7584
Print_ISBN :
1-4244-1209-9
Electronic_ISBN :
1098-7584
Type :
conf
DOI :
10.1109/FUZZY.2007.4295337
Filename :
4295337
Link To Document :
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