This book discusses speaker recognition methods to deal with realistic
variable noisy environments. The text covers authentication systems for;
robust noisy background environments, functions in real time and
incorporated in mobile devices. The book focuses on different approaches
to enhance the accuracy of speaker recognition in presence of varying
background environments. The authors examine: (a) Feature compensation
using multiple background models, (b) Feature mapping using data-driven
stochastic models, (c) Design of super vector- based GMM-SVM framework
for robust speaker recognition, (d) Total variability modeling
(i-vectors) in a discriminative framework and (e) Boosting method to
fuse evidences from multiple SVM models.