Real Time Speaker Recognition System using MFCC and Vector Quantization Technique

Abstract

This paper represents a very strong mathematical algorithm for Automatic Speaker Recognition (ASR) system using MFCC and vector quantization technique in the digital world. MFCC and vector quantization techniques are the most preferable and promising these days so as to support a technological aspect and motivation of the significant progress in the area of voice recognition. Our goal is to develop a real-time speaker recognition system that has been trained for a particular speaker and verifies the speaker. ASR is a type of biometric that uses an individual’s voice for recognition processes. Speaker-vocal discriminative parameters exist in speech signals and due to dissimilar resonances of different speakers speaker recognition system verifies the speaker. These different characteristics can be accomplished by extracting features in vector form like MelFrequency Cepstral Coefficient (MFCCs) from the audio signal. The Vector Quantization (VQ) technique maps vectors from a large vector space to a limited number of regions in the same multidimensional space. LBG (Linde, Buzo and Gray) algorithm is mostly used and preferred for clustering a set of L acoustic vectors into a set of M codebook vectors in speaker recognition.