Wake word based room identification with Personal Voice Assistants

cb
Thumbnail Image
Files
Date
2022
Authors
Azimi, Mohammadreza
Roedig, Utz
Journal Title
Journal ISSN
Volume Title
Publisher
Association for Computing Machinery (ACM)
Published Version
10.5555/3578948.3578990
Research Projects
Organizational Units
Journal Issue
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.
Description
Keywords
Personal Voice Assistants , Wake word , Room identification
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
Link to publisher’s version
https://conferences.jku.at/ewsn2022/
 https://sites.google.com/view/htesp2022/home
URI
https://hdl.handle.net/10468/13382
Collections
Computer Science - Conference Items
Copyright
© 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.