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- W2978782371 abstract "Conventional authentication methods which depend on what the user knows that is usually a password do not guarantee sufficient protection to the information system, because they do not depend on the identity of the authenticated user. The proposed intelligent authentication makes use of digital identity which relies on the concept “who is the user,” and this identity consists of user biometric (voice) attributes, like Mel-frequency cepstral coefficient (MFCC). The proposed authentication approach has two options for feature matching; the first option uses dynamic time warping (DTW) as crisp matching to find the distance between two samples of voice to recognize the identity of an authenticated user (speaker) using MFCC features. The second option uses the fuzzy inner product between fuzzy feature vectors to compute the approaching values between two voice samples using the same features. The experiments are implemented using (ELSDSR) data set, in order to recognize the identity of claimed user. The accuracy of recognition using MFCC with fuzzy vectors was better than recognition using MFCC with dynamic time warping (DTW), and the accuracy of the recognition was 95.45% when using fuzzy logic in MFCC features matching technique." @default.
- W2978782371 created "2019-10-10" @default.
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- W2978782371 date "2019-10-02" @default.
- W2978782371 modified "2023-09-23" @default.
- W2978782371 title "A Proposed Authentication Approach Based on Voice and Fuzzy Logic" @default.
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- W2978782371 doi "https://doi.org/10.1007/978-981-13-9406-5_60" @default.
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