Wake word based room identification with Personal Voice Assistants
dc.contributor.author | Azimi, Mohammadreza | |
dc.contributor.author | Roedig, Utz | |
dc.contributor.funder | Science Foundation Ireland | en |
dc.date.accessioned | 2022-07-20T12:03:46Z | |
dc.date.available | 2022-07-20T12:03:46Z | |
dc.date.issued | 2022 | |
dc.description.abstract | Personal 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.sponsorship | Science Foundation Ireland (Grant number 19/FFP/6775) | en |
dc.description.status | Peer reviewed | en |
dc.description.version | Accepted Version | en |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | Azimi, 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: 10.5555/3578948.3578990 | en |
dc.identifier.doi | 10.5555/3578948.3578990 | |
dc.identifier.uri | https://hdl.handle.net/10468/13382 | |
dc.language.iso | en | en |
dc.publisher | Association for Computing Machinery (ACM) | en |
dc.relation.ispartof | 1st Workshop on Hot Trends in Embedded Systems Privacy (HTESP 2022), Linz, Austria, October 03, 2022 | en |
dc.relation.uri | https://conferences.jku.at/ewsn2022/ | |
dc.relation.uri | https://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.uri | https://creativecommons.org/licenses/by/4.0/ | en |
dc.subject | Personal Voice Assistants | en |
dc.subject | Wake word | en |
dc.subject | Room identification | en |
dc.title | Wake word based room identification with Personal Voice Assistants | en |
dc.type | Conference item | en |
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