Text-Dependent Speaker Recognition

Abstract

Text-dependent speaker recognition textdependent speaker recognition characterizes a speaker recognition task, such as verification or identification, in which the set of words (or lexicon) used during the testing phase is a subset of the ones present during the enrollment phase. The restricted lexicon enables very short enrollment (or registration) and testing sessions to deliver an accurate solution but, at the same time, represents scientific and technical challenges. Because of the short enrollment and testing sessions, text-dependent speaker recognition technology is particularly well suited for deployment in large-scale commercial applications. These are the bases for presenting an overview of the state of the art in text-dependent speaker recognition as well as emerging research avenues. In this chapter, we will demonstrate the intrinsic dependence that the lexical content of the password phrase has on the accuracy. Several research results will be presented and analyzed to show key techniques used in text-dependent speaker recognition systems from different sites. Among these, we mention multichannel speaker model synthesis and continuous adaptation of speaker models with threshold tracking. Since text-dependent speaker recognition is the most widely used voice biometric in commercial deployments, several results drawn from realistic deployment scenarios are also included.