An Overview of Automatic Speaker Verification System

Abstract

Biometrics is used as a form of identification in many access control systems. Some of them are fingerprint, iris, face, speech, and retina. Speech biometrics is used for speaker verification. Speech is the most convenient way to communicate with person and machine, so it plays a vital role in signal processing. Automatic speaker verification is the authentication of individuals by doing analysis on speech utterances. Speaker verification falls into pattern matching problem. Many technologies are used for processing and storing voice prints. Some of them are Frequency Estimation, Hidden Markov Models, Gaussian Mixture Models, Neural Networks, Vector Quantization, and Decision Trees. Mainly speaker verification depends upon speaker modeling and this paper represents a brief overview of the speaker verification system with feature extraction and speaker modeling. Bob spear toolkit is used for evaluation and experiment for the result and analysis. Bob spear is an open-source toolkit for speech processing. For evaluation purpose, three algorithms are proposed which are GMM, ISV, and JFA with the same preprocessing and feature extraction techniques.