Evaluating the use of voice-enabled technologies for ground-truthing activity data

Przemyslaw R Woznowski; Alison Burrows; Pawel Laskowski; Emma L. Tonkin; Ian Craddock

doi:10.1109/PERCOMW.2017.7917546

Evaluating the use of voice-enabled technologies for ground-truthing activity data

Przemyslaw R Woznowski, Alison Burrows, Pawel Laskowski, Emma L. Tonkin, Ian Craddock

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

1 Citation (Scopus)

330 Downloads (Pure)

Abstract

Reliably discerning human activity from sensor data is a nontrivial task in ubiquitous computing, which is central to enabling smart environments. Ground-truth acquisition techniques for such environments can be broadly divided into observational and self-reporting approaches. In this paper we explore one self-reporting approach, using speech-enabled logging to generate ground-truth data. We report the results of a user study in which participants (N=12) used both a smart-watch and a smart-phone app to record their activities of daily living using primarily voice, then answered questionnaires comprising the System Usability Scale (SUS) as well as open ended questions about their experiences. Our findings indicate that even though user satisfaction with the voice-enabled activity logging apps was relatively high, this approach presented significant challenges regarding compliance, effectiveness, and privacy. We discuss the implications of these findings with a view to offering new insights and recommendations for designing systems for ground-truth acquisition ’in the wild’.

Original language	English
Title of host publication	2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops 2017)
Subtitle of host publication	Proceedings of a meeting held 13-17 March 2017, Kona, Big Island, Hawaii, USA
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	135-149
Number of pages	6
ISBN (Electronic)	9781509043385
ISBN (Print)	9781509043392
DOIs	https://doi.org/10.1109/PERCOMW.2017.7917546
Publication status	Published - Jun 2017
Event	1st International Workshop on Annotation of useR Data for UbiquitOUs Systems @ IEEE PerCom 2017 - Kona, Hawaii, United States Duration: 13 Mar 2017 → 17 Mar 2017 http://www.irc-sphere.ac.uk/arduous-workshop

Workshop

Workshop	1st International Workshop on Annotation of useR Data for UbiquitOUs Systems @ IEEE PerCom 2017
Abbreviated title	ARDUOUS
Country	United States
City	Hawaii
Period	13/03/17 → 17/03/17
Internet address	http://www.irc-sphere.ac.uk/arduous-workshop

Structured keywords

Digital Health

Keywords

Ground-truth acquisition
self-annotation
voice- logging
smart-watch app
smart-phone app
activity logging
Digital Health

Access to Document

10.1109/PERCOMW.2017.7917546

Full-text PDF (accepted author manuscript)
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Accepted author manuscript, 3.14 MBLicence: Unspecified

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1 Finished

SPHERE (EPSRC IRC)
Craddock, I. J., Coyle, D. T., Flach, P. A., Kaleshi, D., Mirmehdi, M., Piechocki, R. J., Stark, B. H., Ascione, R., Ashburn, A. M., Burnett, M. E., Damen, D., Gooberman-Hill, R. J. S., Harwin, W. S., Hilton, G., Holderbaum, W., Holley, A. P., Manchester, V. A., Meller, B. J., Stack, E. & Gilchrist, I. D.
1/10/13 → 30/09/18
Project: Research, Parent

Cite this

Woznowski, P. R., Burrows, A., Laskowski, P., Tonkin, E. L., & Craddock, I. (2017). Evaluating the use of voice-enabled technologies for ground-truthing activity data. In 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops 2017): Proceedings of a meeting held 13-17 March 2017, Kona, Big Island, Hawaii, USA (pp. 135-149). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/PERCOMW.2017.7917546

Woznowski, Przemyslaw R ; Burrows, Alison ; Laskowski, Pawel ; Tonkin, Emma L. ; Craddock, Ian. / Evaluating the use of voice-enabled technologies for ground-truthing activity data. 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops 2017): Proceedings of a meeting held 13-17 March 2017, Kona, Big Island, Hawaii, USA. Institute of Electrical and Electronics Engineers (IEEE), 2017. pp. 135-149

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abstract = "Reliably discerning human activity from sensor data is a nontrivial task in ubiquitous computing, which is central to enabling smart environments. Ground-truth acquisition techniques for such environments can be broadly divided into observational and self-reporting approaches. In this paper we explore one self-reporting approach, using speech-enabled logging to generate ground-truth data. We report the results of a user study in which participants (N=12) used both a smart-watch and a smart-phone app to record their activities of daily living using primarily voice, then answered questionnaires comprising the System Usability Scale (SUS) as well as open ended questions about their experiences. Our findings indicate that even though user satisfaction with the voice-enabled activity logging apps was relatively high, this approach presented significant challenges regarding compliance, effectiveness, and privacy. We discuss the implications of these findings with a view to offering new insights and recommendations for designing systems for ground-truth acquisition {\textquoteright}in the wild{\textquoteright}.",

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Woznowski, PR, Burrows, A, Laskowski, P, Tonkin, EL & Craddock, I 2017, Evaluating the use of voice-enabled technologies for ground-truthing activity data. in 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops 2017): Proceedings of a meeting held 13-17 March 2017, Kona, Big Island, Hawaii, USA. Institute of Electrical and Electronics Engineers (IEEE), pp. 135-149, 1st International Workshop on Annotation of useR Data for UbiquitOUs Systems @ IEEE PerCom 2017, Hawaii, United States, 13/03/17. https://doi.org/10.1109/PERCOMW.2017.7917546

Evaluating the use of voice-enabled technologies for ground-truthing activity data. / Woznowski, Przemyslaw R; Burrows, Alison; Laskowski, Pawel; Tonkin, Emma L.; Craddock, Ian.

2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops 2017): Proceedings of a meeting held 13-17 March 2017, Kona, Big Island, Hawaii, USA. Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 135-149.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Evaluating the use of voice-enabled technologies for ground-truthing activity data

AU - Woznowski, Przemyslaw R

AU - Burrows, Alison

AU - Laskowski, Pawel

AU - Tonkin, Emma L.

AU - Craddock, Ian

PY - 2017/6

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N2 - Reliably discerning human activity from sensor data is a nontrivial task in ubiquitous computing, which is central to enabling smart environments. Ground-truth acquisition techniques for such environments can be broadly divided into observational and self-reporting approaches. In this paper we explore one self-reporting approach, using speech-enabled logging to generate ground-truth data. We report the results of a user study in which participants (N=12) used both a smart-watch and a smart-phone app to record their activities of daily living using primarily voice, then answered questionnaires comprising the System Usability Scale (SUS) as well as open ended questions about their experiences. Our findings indicate that even though user satisfaction with the voice-enabled activity logging apps was relatively high, this approach presented significant challenges regarding compliance, effectiveness, and privacy. We discuss the implications of these findings with a view to offering new insights and recommendations for designing systems for ground-truth acquisition ’in the wild’.

AB - Reliably discerning human activity from sensor data is a nontrivial task in ubiquitous computing, which is central to enabling smart environments. Ground-truth acquisition techniques for such environments can be broadly divided into observational and self-reporting approaches. In this paper we explore one self-reporting approach, using speech-enabled logging to generate ground-truth data. We report the results of a user study in which participants (N=12) used both a smart-watch and a smart-phone app to record their activities of daily living using primarily voice, then answered questionnaires comprising the System Usability Scale (SUS) as well as open ended questions about their experiences. Our findings indicate that even though user satisfaction with the voice-enabled activity logging apps was relatively high, this approach presented significant challenges regarding compliance, effectiveness, and privacy. We discuss the implications of these findings with a view to offering new insights and recommendations for designing systems for ground-truth acquisition ’in the wild’.

KW - Ground-truth acquisition

KW - self-annotation

KW - voice- logging

KW - smart-watch app

KW - smart-phone app

KW - activity logging

KW - Digital Health

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DO - 10.1109/PERCOMW.2017.7917546

M3 - Conference Contribution (Conference Proceeding)

SN - 9781509043392

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EP - 149

BT - 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops 2017)

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 1st International Workshop on Annotation of useR Data for UbiquitOUs Systems @ IEEE PerCom 2017

Y2 - 13 March 2017 through 17 March 2017

ER -

Woznowski PR, Burrows A, Laskowski P, Tonkin EL , Craddock I. Evaluating the use of voice-enabled technologies for ground-truthing activity data. In 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops 2017): Proceedings of a meeting held 13-17 March 2017, Kona, Big Island, Hawaii, USA. Institute of Electrical and Electronics Engineers (IEEE). 2017. p. 135-149 https://doi.org/10.1109/PERCOMW.2017.7917546

Evaluating the use of voice-enabled technologies for ground-truthing activity data

Abstract

Workshop

Structured keywords

Keywords

Access to Document

SPHERE (EPSRC IRC)

Cite this