saeed vandaki - Islamic Azad University, Gonabad Branch,
saman zahiri rad - Islamic Azad University, Gonabad Branch,
naser mehrshad - Islamic Azad University, Gonabad Branch,

In any language, Spoken alphabet identification as one of the subsets ofspeech identificationand pattern identification has many applications. However, it is noteasy to recognize the alphabet. Similar sound that is difficult to detect. One of the problems set is called the E-set that include words letters B, C, D, E, G, P, T, Vand Z. This paper describes an approach of speech identification by using the Mel-Scale Frequency Cepstral Coefficients (MFCC) extracted from speech signal of spoken words. The Support Vector Machine (SVM) is used as classifier. In this paper, a method issaid to have achieved %08 accuracy on data-set TI ALPHA.

Mel-frequency cepstral coefficients, (MFCC),Support Vector Machines(SVMs