Paper Title
Speaker Recognition Using Support Vector Machines

Abstract— Recently Support Vector machines are being used in a wide variety of classification purposes. This paper explores the usage of SVM’s in the binary classification of speaker, as in between the original speaker and an imposter. The feature vector used for the extraction of features is MFCC’s i.e. Mel Frequency Cepstrum Coefficients. The paper further explores the usage of Principle Component analysis for dimensionality reduction.