Perception of Privacy Measured in the Crowd−Paired Comparison on the Effect of Background Noises

Anna Leschanowsky, Sneha Das, Tom Bäckström, Pablo Perez Zarazaga

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

2 Citations (Scopus)
106 Downloads (Pure)


Voice based devices and virtual assistants are widely integrated into our daily life, but the growing popularity has also raised concerns about data privacy in processing and storage. While improvements in technology and data protection regulations have been made to provide users a more secure experience, the concept of privacy continues to be subject to enormous challenges. We can observe that people intuitively adjust their way of talking in a human-to-human conversation, an intuition that devices could benefit from to increase their level of privacy. In order to enable devices to quantify privacy in an acoustic scenario, this paper focuses on how people perceive privacy with respect to environmental noise. We measured privacy scores on a crowdsourcing platform with a paired comparison listening test and obtained reliable and consistent results. Our measurements show that the experience of privacy varies depending on the acoustic features of the ambient noise. Furthermore, multiple probabilistic choice models were fitted to the data to obtain a meaningful ordering of noise scenarios conveying listeners' preferences. A preference tree model was found to fit best, indicating that subjects change their decision strategy depending on the scenarios under test.
Original languageEnglish
Title of host publicationProceedings of Interspeech
PublisherInternational Speech Communication Association (ISCA)
Number of pages5
Publication statusPublished - 2020
MoE publication typeA4 Conference publication
EventInterspeech - Shanghai, China
Duration: 25 Oct 202029 Oct 2020
Conference number: 21

Publication series

ISSN (Electronic)1990-9772


Abbreviated titleINTERSPEECH
Internet address


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