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- W2370639217 abstract "A Chinese speech(mandarin) database was established for speakers gender recognition.A combination method is proposed for gender recognition of speakers based on support vector machine and Mel-frequency cepstrum coefficients(MFCC) for classification and feature extraction respectively.The comparative result shows that the accuracy of SVM is 98.7%,which is better than other methods." @default.
- W2370639217 created "2016-06-24" @default.
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- W2370639217 date "2009-01-01" @default.
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- W2370639217 title "Gender recognition of speakers based on MFCC and SVM" @default.
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