Speaker Recognition Using MFCC &Evolution with Different Classification Techniques
Journal Title: International Journal of Engineering and Science Invention - Year 2017, Vol 6, Issue 9
Abstract
This research paper is designed a unimodal biometric system based on speaker recognition. TheMel-Frequency Cepstral Coefficients (MFCC)is used for extracting the voice features. We applied this technique for identification of a person on KVKRG voice database. For this experiment, 500 phonemes of 50 subjects from KVKRG voice database were used. The database consists of phoneme in language spoken in multimodal biometrics research lab, Dept. of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University Aurangabad of Maharashtra. The phoneme of each subject is collected five times i.e. English alphabets (a – z) and five times i.e. digits (0 – 10).Three samples used for training and the rest two used for testing. Different classifiers were used like Linear Discriminate, SVM, k-NN, Ensemble Subspace Discriminate. The recognition rate for (a-z) is 98% and (0-10) is 96%. Experimental result shows that biometrics system gives improvement in the overall system performance, results quickly and accurate.
Authors and Affiliations
Pravin G. Sarpate, Ramesh R. Manza
Keywords
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