SPEAKER BASED IDENTIFICATION SYSTEM

Abstract

Nowadays it is obvious that speakers can be identified from their voices. In this work we look into the details of speaker identification from the real-time system point of view. Firstly, we review the well-known techniques used in speaker identification. We look into the details of every step in identification process and explain the ideas, which leaded to these techniques. We start from the basic definitions used in DSP, then we move to the feature extraction step and review two types of features, namely MFCC and LPCC, and finally we review two speaker modeling techniques, VQ and GMM. Secondly, we analyze described techniques from the time complexity point of view and propose several approaches to their optimization. Finally, we propose a novel approach to the feature matching step in the speaker identification and analyze it theoretically. The main objective of this approach is an iterative pruning of speaker models, which are far away from the unknown speech sample, during the identification process. Which is greatly improves identification speed in feature matching step. [