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- W2372055584 abstract "Because supporting vectors are near to the border,before training speaker identification system based on SVM using speech training assemble,it is needed to reduce the training assemble.Because the training assemble are tremendous and non-linear,a concept called sub-clusters reduced SVM is presented.Firstly,this paper uses kernel-based fuzzy sub-clusters to filter the non-border cluster areas,then cuts the redundant vectors within the remaining cluster areas.Theory and experimental results show that the time and storage efficiency can be enhanced remarkably by using the training and identifying algorithm,and the system has better robustness." @default.
- W2372055584 created "2016-06-24" @default.
- W2372055584 creator A5086867190 @default.
- W2372055584 date "2010-01-01" @default.
- W2372055584 modified "2023-09-26" @default.
- W2372055584 title "Speaker identification based on sub-clusters reduced SVM" @default.
- W2372055584 hasPublicationYear "2010" @default.
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