International Journal of Scientific and Research Publications

IJSRP, Volume 5, Issue 11, November 2015 Edition [ISSN 2250-3153]


Electronic disguised voice identification based on Mel-Frequency Cepstral Coefficient analysis
      Shalate D’cunha, Shefeena P.S
Abstract: In this paper, the proposed method is mainly based on analyzing the mel-frequency cepstral coefficients and its derivatives which varies as the voice is disguised. A classifier named the Support Vector Machine (SVM) classifier is used for identification of electronically disguised voice. MFCC statistical moments of training input and test input as a combination of original voice and disguised voice, are given as input to SVM classifier. Now the output obtained will be based on the matching between the training input and the test input. Inorder to provide further enhancement to the particular algorithm, probabilistic neural network(PNN) classifier is used and the performance is evaluated by comparing the accuracy of both classifiers. If the classifier output is matched, then the basic details of the particular person can be transmitted to another location through Email.

Reference this Research Paper (copy & paste below code):

Shalate D’cunha, Shefeena P.S (2018); Electronic disguised voice identification based on Mel-Frequency Cepstral Coefficient analysis; Int J Sci Res Publ 5(11) (ISSN: 2250-3153). http://www.ijsrp.org/research-paper-1115.php?rp=P474807
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