Speaker Recognition Systems in the Last Decade – A Survey
Speaker Recognition Defined by the process of recognizing a person by his\her voice through specific features that extract from his\her voice signal. An Automatic Speaker recognition (ASP) is a biometric authentication system. In the last decade, many advances in the speaker recognition field have been attained, along with many techniques in feature extraction and modeling phases. In this paper, we present an overview of the most recent works in ASP technology. The study makes an effort to discuss several modeling ASP techniques like Gaussian Mixture Model GMM, Vector Quantization (VQ), and Clustering Algorithms. Also, several feature extraction techniques like Linear Predictive Coding (LPC) and Mel frequency cepstral coefficients (MFCC) are examined. Finally, as a result of this study, we found MFCC and GMM methods could be considered as the most successful techniques in the field of speaker recognition so far.
How to Cite
The author assigns to Engineering and Technology Journal with full title guarantee, all copyrights, rights in the nature of copyright, and all other intellectual property rights in the article throughout the world (present and future, and including all renewals, extensions, revivals, restorations and accrued rights of action). The Author represents that he/she is the author and proprietor of this Article and that this Article has not heretofore been published in any form. The Author warrants that he/she has obtained written permission and paid all fees for use of any literary or illustration material for which rights are held by others. The author agrees to hold the editor(s)/publisher harmless against any suit, demand, claim or recovery, finally sustained, by reason of any violation of proprietary right or copyright, or any unlawful matter contained in the submitted article.