Abstract
A subword-based, text-dependent speaker verification system that embodies the capability of user-selectable passwords (ideally, with no constraints on the choice of vocabulary words or the language) is presented. A novel automatic speech segmentation procedure, called the "blind" segmentation, is also introduced. This algorithm segments speech without any linguistic knowledge and makes the subword modeling of the user-selectable password realizable in the proposed system. The subword modeling is done using the neural tree networks (NTNs). The NTN is a hierarchical classifier that combines the properties of decision trees and feed-forward neural networks. The proposed system also takes advantage of such concepts as the multiple classifier fusion and data resampling to successfully boost the system performance.