Spoofing detection for personal voice assistants

Simple item page
dc.contributor.authorSankar, M. S. Arun en
dc.contributor.authorDe Leon, Phillip L.en
dc.contributor.authorRoedig, Utzen
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2023-11-13T12:38:02Z
dc.date.available2023-11-13T12:38:02Z
dc.date.issued2023-11-13en
dc.description.abstractPersonal Voice Assistants (PVAs) are common acoustic sensing systems that are used as a speech-based controller for critical systems making them vulnerable to speech spoofing attacks. Prior research has focused on the discrimination of genuine and spoofed speech for applications with large population speaker verification and challenges such as ASVspoof have advanced this work over the last few years. In this paper, we consider spoofing detection in a PVA setting where the number of household users is small. We show that when pre-trained models are adapted to household users, spoofing detection is improved. Furthermore, we demonstrate that adaptation is still effective in realistic scenarios where only genuine speech of household users is available but the generation of spoofed speech samples for household users is undesirable.en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationSankar, A. M. S., De Leon, P. and Roedig, U. (2023) 'Spoofing Detection for Personal Voice Assistants', 21st ACM Conference on Embedded Networked Sensor Systems (SenSys ’23), Istanbul, Turkiye, November 12-17. ACM, New York, NY, USA, (2 pp).en
dc.identifier.endpage7en
dc.identifier.isbn979-8-4007-0414-7/23/11
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/15223
dc.language.isoenen
dc.publisherACMen
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Frontiers for the Future::Award/19/FFP/6775/IE/Personal Voice Assistant Security and Privacy/en
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres Programme::Phase 2/13/RC/2077_P2/IE/CONNECT_Phase 2/en
dc.rights© 2023 the authors. For the purpose of Open Access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission; Published version © 2023 Association for Computing Machinery.en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectComputer securityen
dc.subjectAcoustic sensingen
dc.subjectBiometricsen
dc.subjectSpeaker recognitionen
dc.subjectSpeech processingen
dc.subjectSystem securityen
dc.subjectPrivacyen
dc.subjectSecurityen
dc.subjectInternet of Things (IoT)en
dc.titleSpoofing detection for personal voice assistantsen
dc.typeConference itemen
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Sensors_S_P_Spoofing_Detection.pdf
Size:
547.41 KB
Format:
Adobe Portable Document Format
Description:
Accepted version
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
2.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Computer Science - Conference Items