Journal of Al-Qadisiyah for Computer Science and Mathematics

Abstract

Automatic speaker recognition systems use the machines to recognize an individual via a spoken sentence. Those systems recognize a specific individual or confirm an individual’s claimed identity. The most common type of voice biometrics is the Speaker Recognition. Its task focused on validation of a person’s claimed identity, using features that have been obtained via their voices. Throughout the last decades a wide range of new advances in the speaker recognition area have been accomplished, but there are still many problems that need solving or require enhanced solutions. In this paper, a brief overview of speech processing is given firstly, then some feature extraction and classifier techniques are described, also a comparative and analysis of some previous research are studied in depth, all this work leads to determine the best methods for speaker recognition. Adaptive MFCC and Deep Learning methods are determined to be more efficient and accurate than other methods in speaker recognition, thus these methods are recommend to be more suitable for practical applications.