This document discusses a method for speaker identification and verification using Mel Frequency Cepstral Coefficients (MFCC) and Support Vector Machines (SVM). MFCC is used to extract features from speech samples, representing the spectral properties of the voice. SVM is then used to match these features between speech samples to identify or verify speakers. The authors claim this method can identify speakers with up to 95% accuracy and is computationally efficient. It is proposed that MFCC and SVM outperform other techniques for speaker recognition tasks. The system is described as having applications in security, voice interfaces, and other voice-based systems.