A person's voice contains various parameters that convey information such as emotion, gender, attitude, health and identity. This paper talks about speaker recognition which deals with the subject of identifying a person based on their unique voiceprint present in their speech data. Pre-processing of the speech signal is performed before voice feature extraction. This process ensures the voice feature extraction contains accurate information that conveys the identity of the speaker. Voice feature extraction methods such as Linear Predictive Coding (LPC), Linear Predictive Cepstral Co-efficient (LPCC) and Mel-Frequency Cepstral Co-efficient (MFCC) are analyzed and evaluated for their suitability for use in speaker recognition tasks.