Speaker verification for telemedical applications

Author

Buch, Ojas A. ; Reddy, Narender P.

Author_Institution

Dept. of Biomed. Eng., Akron Univ., OH, USA

Volume

2

fYear

1997

fDate

30 Oct-2 Nov 1997

Firstpage

902

Abstract

A major problem in telemedical applications is the confidentiality and secured access to patient/medical records. The purpose of this investigation was to develop neural network models for speech-based speaker verification. Speech data was analyzed and fed to several neural networks. Based on the performance of the initial testing, the best five networks were recruited into the committee. The majority opinion of the committee was used to classify the designated individual and the imposters. The committee correctly verified the designated individual in 100% of the cases and rejected the imposters in 100% of the cases. The committee networks-based user verification has a significant potential for telemedical applications

Keywords

neural nets; pattern classification; speaker recognition; telemedicine; confidentiality; imposters; majority opinion; medical records; neural network committee; patient records; performance; secured access; speaker classification; speech-based speaker verification; telemedical applications; Band pass filters; Biomedical imaging; Digital filters; Feature extraction; Frequency; Mathematical model; Neural networks; Signal processing; Speech analysis; Telemedicine;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1997. Proceedings of the 19th Annual International Conference of the IEEE

Conference_Location

Chicago, IL

ISSN

1094-687X

Print_ISBN

0-7803-4262-3

Type

conf

DOI

10.1109/IEMBS.1997.757813

Filename

757813