Kevin R. Farrell

Learn More
An evaluation of various classifiers for textindependent speaker recognition is presented. In addition, a new classifier is examined for this application. The new classifier is called the modified neural tree network (MNTN). The MNTN is a hierarchical classifier that combines the properties of decision trees and feedforward neural networks. The MNTN differs(More)
Speaker recognition refers to the concept of recognizing a speaker by his=her voice or speech samples. Some of the important applications of speaker recognition include customer veri cation for bank transactions, access to bank accounts through telephones, control on the use of credit cards, and for security purposes in the army, navy and airforce. This(More)
Zinc is a common supplement and is widely available as a standard component of many over-the-counter products. A number of reports have identified an association between excessive zinc intake and severe cytopenia. We report a case of zinc-induced copper deficiency in a young adult to illustrate this under-recognized cause of anemia and neutropenia.
The purpose of this study was to examine the intertester and intratester reliability of hand volumetric measurements comparing two different protocols. The first protocol involved three clinicians at an outpatient facility interpreting the manufacturer's volumeter instructions. At the second university site, three testers utilized a modified version of the(More)
In this paper, we analyze the diversity of information as provided by several modeling approaches for speaker verification. This information is used to facilitate the fusion of the individual results into an overall result that provides advantages in accuracy over the individual models. The modeling methods that are evaluated consist of the neural tree(More)
Mismatched training and testing conditions for speaker recognition exist when speech is subjected to a different channel for both cases. This results in diminished speaker recognition performance. Estimating and removing the channel filtering effect will make speaker recognition systems more robust. It has been shown that a reliable estimate is obtained by(More)