University of Hertfordshire

By the same authors

Effectiveness in the Realisation of Speaker Authentication

Research output: Chapter in Book/Report/Conference proceedingConference contribution


View graph of relations
Original languageEnglish
Title of host publication2019 International Carnahan Conference on Security Technology (ICCST), CHENNAI, India, 2019
Subtitle of host publicationIEEE ICCST 2019
Number of pages5
ISBN (Electronic)9781728115764
ISBN (Print)978-1-7281-1575-7
Publication statusPublished - 31 Oct 2019
EventThe IEEE (53rd) International Carnahan Conference on Security Technology - Anna University, Chennai, India
Duration: 1 Oct 20193 Oct 2019

Publication series

NameProceedings - International Carnahan Conference on Security Technology
ISSN (Print)1071-6572


ConferenceThe IEEE (53rd) International Carnahan Conference on Security Technology
Internet address


An important consideration for the deployment of speaker recognition in authentication applications is the approach to the formation of training and testing utterances . Whilst defining this for a specific scenario is influenced by the associated requirements and conditions, the process can be further guided through the establishment of the relative usefulness of alternative frameworks for composing the training and testing material. In this regard, the present paper provides an analysis of the effects, on the speaker recognition accuracy, of various bases for the formation of the training and testing data. The experimental investigations are conducted based on the use of digit utterances taken from the XM2VTS database. The paper presents a detailed description of the individual approaches considered and discusses the experimental results obtained in different cases.


© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

ID: 17567407