Assessing the feasibility of speech-based activity recognition in dynamic medical settings

Swathi Jagannath, Aleksandra Sarcevic, Neha Kamireddi, Ivan Marsic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We describe an experiment conducted with three domain experts to understand how well they can recognize types and performance stages of activities using speech data transcribed from verbal communications during dynamic medical teamwork. The insights gained from this experiment will inform the design of an automatic activity recognition system to alert medical teams to process deviations in real time. We contribute to the literature by (1) characterizing how domain experts perceive the dynamics of activity-related speech, and (2) identifying the challenges associated with system design for speech-based activity recognition in complex team-based work settings.

Original languageEnglish (US)
Title of host publicationCHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450359719
DOIs
StatePublished - May 2 2019
Event2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019 - Glasgow, United Kingdom
Duration: May 4 2019May 9 2019

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019
CountryUnited Kingdom
CityGlasgow
Period5/4/195/9/19

Fingerprint

Experiments
Systems analysis
Communication

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

Keywords

  • Activity recognition
  • Decision support
  • Emergency medicine
  • Narrative schema
  • Speech analysis
  • Speech modeling

Cite this

Jagannath, S., Sarcevic, A., Kamireddi, N., & Marsic, I. (2019). Assessing the feasibility of speech-based activity recognition in dynamic medical settings. In CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems [3312983] (Conference on Human Factors in Computing Systems - Proceedings). Association for Computing Machinery. https://doi.org/10.1145/3290607.3312983
Jagannath, Swathi ; Sarcevic, Aleksandra ; Kamireddi, Neha ; Marsic, Ivan. / Assessing the feasibility of speech-based activity recognition in dynamic medical settings. CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2019. (Conference on Human Factors in Computing Systems - Proceedings).
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Jagannath, S, Sarcevic, A, Kamireddi, N & Marsic, I 2019, Assessing the feasibility of speech-based activity recognition in dynamic medical settings. in CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems., 3312983, Conference on Human Factors in Computing Systems - Proceedings, Association for Computing Machinery, 2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019, Glasgow, United Kingdom, 5/4/19. https://doi.org/10.1145/3290607.3312983

Assessing the feasibility of speech-based activity recognition in dynamic medical settings. / Jagannath, Swathi; Sarcevic, Aleksandra; Kamireddi, Neha; Marsic, Ivan.

CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2019. 3312983 (Conference on Human Factors in Computing Systems - Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Jagannath S, Sarcevic A, Kamireddi N, Marsic I. Assessing the feasibility of speech-based activity recognition in dynamic medical settings. In CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery. 2019. 3312983. (Conference on Human Factors in Computing Systems - Proceedings). https://doi.org/10.1145/3290607.3312983