Speaker Recognition Systems in the Last Decade – A Survey | ||
| Engineering and Technology Journal | ||
| Article 4, Volume 39, 1B, March 2021, Pages 30-40 PDF (487.01 K) | ||
| DOI: 10.30684/etj.v39i1B.1589 | ||
| Authors | ||
| Ahmed M. Ahmed* 1; Aliaa K. Hassan2 | ||
| 1University of Technology, Baghdad, Iraq, 110172@student.uotechnology.edu.iq | ||
| 2University of Technology, Baghdad, Iraq, 110018@uotechnology.edu.iq | ||
| Abstract | ||
| 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. | ||
| Keywords | ||
| Speaker Recognition; speaker identification; MFCC; and Feature Extraction | ||
|
Statistics Article View: 377 PDF Download: 308 |
||