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