Adoption Speaker Recognition System using Mel-frequency Cepstral Coefficients

Reda Elbarougy, G behery, Hanan A. Algrbaa

Abstract


The traditional system of speaker recognition depends on extraction some of features within the speech. Many researchers have adopted several ways to extract these features. One of the most famous of these methods is MFCC. The number of extracted features using MFCC ranges from 2 to 13 feature. The number of extracted features not enough to deal with our problem. This paper presented an adoptive MFCC range from 2 to 91 features to the MFCC. The adoptive MFCC gave us the features instead of 13 that certainly gave a great opportunity to distinguish between speakers. The extracted features were used in the process of classifying speakers using GMM and NNT the proposed system is very efficiency where some speakers were fully recognized.


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