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A Taxonomy of Noise in Voice Self-reports while Running

Bi, Tao; Olugbade, Temitayo; Mathur, Akhil; Holloway, Catherine; Singh, Aneesha; Costanza, Enrico; Berthouze, nadia; (2022) A Taxonomy of Noise in Voice Self-reports while Running. In: Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp/ISWC '22 Adjunct). ACM: Association for Computing Machinery: Cambridge, UK. (In press). Green open access

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Abstract

Smart earables offer great opportunities for conducting ubiquitous computing research. This paper shares its reflection on collecting self-reports from runners using the microphone on the smart eSense earbud device. Despite the advantages of the eSense in allowing researchers to collect continuous voice self-reports anytime anywhere, it also captured noise signals from various sources and created challenges in data processing and analysis. The paper presents an initial taxonomy of noise in runners’ voice self-reports data via eSense. This is based on a qualitative analysis of voice recordings based on eSense’s microphone with 11 runners across 14 in-the-wild running sessions. The paper discusses the details and characteristics of the observed noise, the challenges in achieving good-quality self-reports, and opportunities for extracting useful contextual information. The paper further suggests a noise-categorization API for the eSense or other similar platforms, not only for the purpose of noise-cancellation but also incorporating the mining of contextual information.

Type: Proceedings paper
Title: A Taxonomy of Noise in Voice Self-reports while Running
Event: 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp/ISWC '22 Adjunct),
Location: Cambridge, United Kingdom
Dates: 12 Sep 2022 - 15 Sep 2022
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3544793.3563421
Publisher version: https://doi.org/10.1145/3544793.3563421
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10155651
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