JCP 2012 Vol.7(9): 2269-2275 ISSN: 1796-203X
doi: 10.4304/jcp.7.9.2269-2275
doi: 10.4304/jcp.7.9.2269-2275
Speech Recognition Approach Based on Speech Feature Clustering and HMM
XinGuang Li, MinFeng Yao, JiaNeng Yang
Guangdong University of Foreign Studies, Guangzhou, 510006, China
Abstract—The paper presents a Segment-Mean method for reducing the dimension of the speech feature parameters. K-Means function is used to group the speech feature parameters whose dimension has been reduced. And then the speech samples are classified into different clusters according to their features. It proposes a cross-group training algorithm for the speech feature parameters clustering which improves the accuracy of the clustering function. When recognizing speech, the system uses a crossgroup HMM models algorithm to match patterns which reduces the calculation by more than 50% and without reducing the recognition rate of the small vocabulary speech recognition system.
Index Terms—HMM, Speech Feature Parameters, Segment- Mean, K-Means Clustering, Model Cross-group.
Abstract—The paper presents a Segment-Mean method for reducing the dimension of the speech feature parameters. K-Means function is used to group the speech feature parameters whose dimension has been reduced. And then the speech samples are classified into different clusters according to their features. It proposes a cross-group training algorithm for the speech feature parameters clustering which improves the accuracy of the clustering function. When recognizing speech, the system uses a crossgroup HMM models algorithm to match patterns which reduces the calculation by more than 50% and without reducing the recognition rate of the small vocabulary speech recognition system.
Index Terms—HMM, Speech Feature Parameters, Segment- Mean, K-Means Clustering, Model Cross-group.
Cite: XinGuang Li, MinFeng Yao, JiaNeng Yang, "Speech Recognition Approach Based on Speech Feature Clustering and HMM," Journal of Computers vol. 7, no. 9, pp. 2269-2275, 2012.
General Information
ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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