TY - JOUR
T1 - An overview of statistical pattern recognition techniques for speaker verification
AU - Fazel, Amin
AU - Chakrabartty, Shantanu
N1 - Funding Information:
This work was supported in part by a grant from the National Science Foundation: IIS:0836278.
Funding Information:
B.Tech. degree from Indian Institute of Technology, Delhi in 1996, M.S. and Ph.D. in Electrical Engineering from Johns Hopkins University, Baltimore, MD in 2002 and 2005 respectively. He is currently an associate professor in the department of electrical and computer engineering at Michigan State University. From 1996–1999 he was with Qualcomm Incorporated, San Diego and during 2002 he was a visiting researcher at The University of Tokyo. His current research interests include energy scavenging sensors and integrated circuits, hybrid circuits and systems and ultra-low power analog signal processing circuits. Dr. Chakrabartty is a recipient of the National Science Foundation CAREER award, Michigan State University’s teacher-scholar award and a catalyst foundation fellowship from 1999–2003. He has published more than 80 refereed articles and is a senior member of the Institute of Electrical and Electronics Engineers (IEEE). He has served or is currently serving as the associate editor of IEEE Transactions of Biomedical Circuits and Systems, associate editor for Advances in Artificial Neural Systems journal and a review editor for Frontiers of Neu-romorphic Engineering journal.
PY - 2011/6
Y1 - 2011/6
N2 - Even though the subject of speaker verification has been investigated for several decades, numerous challenges and new opportunities in robust recognition techniques are still being explored. In this overview paper we first provide a brief introduction to statistical pattern recognition techniques that are commonly used for speaker verification. The second part of the paper presents traditional and modern techniques which make real-world speaker verification systems robust in degradation due to the presence of ambient noise; channel variations, aging effects, and availability of limited training samples. The paper concludes with discussions on future trends and research opportunities in this area.
AB - Even though the subject of speaker verification has been investigated for several decades, numerous challenges and new opportunities in robust recognition techniques are still being explored. In this overview paper we first provide a brief introduction to statistical pattern recognition techniques that are commonly used for speaker verification. The second part of the paper presents traditional and modern techniques which make real-world speaker verification systems robust in degradation due to the presence of ambient noise; channel variations, aging effects, and availability of limited training samples. The paper concludes with discussions on future trends and research opportunities in this area.
UR - http://www.scopus.com/inward/record.url?scp=79958843193&partnerID=8YFLogxK
U2 - 10.1109/MCAS.2011.941080
DO - 10.1109/MCAS.2011.941080
M3 - Review article
AN - SCOPUS:79958843193
SN - 1531-636X
VL - 11
SP - 62
EP - 81
JO - IEEE Circuits and Systems Magazine
JF - IEEE Circuits and Systems Magazine
IS - 2
M1 - 5871480
ER -