Wake word based room identification with Personal Voice Assistants

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dc.contributor.authorAzimi, Mohammadreza
dc.contributor.authorRoedig, Utz
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2022-07-20T12:03:46Z
dc.date.available2022-07-20T12:03:46Z
dc.date.issued2022
dc.description.abstractPersonal Voice Assistants (PVAs) are used to interact with digital environments and computer systems using speech. A wake word such as ’Alexa’ is spoken by the user to initiate interaction with the PVA. We use the audio recording of the wake word to determine the room in which user - PVA interaction takes place. We collected data from 10 different rooms in which a user speaks the wake word at different lo- cations. This dataset is used to evaluate three different neural network based algorithms for room identification. Our evaluation shows that rooms can be identified with 90% accuracy. The impact is twofold: (i) PVA audio recordings leak private information about the user environment; (ii) Acoustic room identification is an option for augmenting user - PVA interaction.en
dc.description.sponsorshipScience Foundation Ireland (Grant number 19/FFP/6775)en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationAzimi, M. and Roedig, U. (2022) 'Wake word based room identification with Personal Voice Assistants',EWSN '22: Proceedings of the 2022 International Conference on Embedded Wireless Systems and Networks, Linz, Austria, 3-5 October, pp. 262–267. doi: 10.5555/3578948.3578990en
dc.identifier.doi10.5555/3578948.3578990
dc.identifier.urihttps://hdl.handle.net/10468/13382
dc.language.isoenen
dc.publisherAssociation for Computing Machinery (ACM)en
dc.relation.ispartof1st Workshop on Hot Trends in Embedded Systems Privacy (HTESP 2022), Linz, Austria, October 03, 2022en
dc.relation.urihttps://conferences.jku.at/ewsn2022/
dc.relation.urihttps://sites.google.com/view/htesp2022/home
dc.rights© 2022, Association for Computing Machinery. This is the author's version of the work. The definitive Version of Record is available at: https://dx.doi.org/10.5555/3578948.3578990. For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectPersonal Voice Assistantsen
dc.subjectWake worden
dc.subjectRoom identificationen
dc.titleWake word based room identification with Personal Voice Assistantsen
dc.typeConference itemen
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