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It is Okay to be Distracted: How Real-time Transcriptions Facilitate Online Meeting with Distraction

Title
It is Okay to be Distracted: How Real-time Transcriptions Facilitate Online Meeting with Distraction
Author(s)
Son, SeoyunChoi, JunyougLee, SunjaeSong, Jean YoungShin, Insik
Issued Date
2023-04-24
Citation
ACM Conference on Human Factors in Computing Systems, pp.1 - 19
Type
Conference Paper
ISBN
9781450394215
Abstract
Online meetings are indispensable in collaborative remote work environments, but they are vulnerable to distractions due to their distributed and location-agnostic nature. While distraction often leads to a decrease in online meeting quality due to loss of engagement and context, natural multitasking has positive tradeoff effects, such as increased productivity within a given time unit. In this study, we investigate the impact of real-time transcriptions (i.e., full-transcripts, summaries, and keywords) as a solution to help facilitate online meetings during distracting moments while still preserving multitasking behaviors. Through two rounds of controlled user studies, we qualitatively and quantitatively show that people can better catch up with the meeting flow and feel less interfered with when using real-time transcriptions. The benefits of real-time transcriptions were more pronounced after distracting activities. Furthermore, we reveal additional impacts of real-time transcriptions (e.g., supporting recalling contents) and suggest design implications for future online meeting platforms where these could be adaptively provided to users with different purposes. © 2023 ACM.
URI
http://hdl.handle.net/20.500.11750/46771
DOI
10.1145/3544548.3580742
Publisher
Association for Computing Machinery
Related Researcher
  • 송진영 Song, Jean Young
  • Research Interests 인간-기계 상호작용; 인간-AI 상호작용; 크라우드소싱; 인공지능 데이터셋; 컴퓨터비전; Human-Computer Interaction; Artificial Intelligence; Human-AI Collaboration; Crowdsourcing; Computer Vision
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Appears in Collections:
Department of Electrical Engineering and Computer Science DGIST Intelligence Augmentation Group 2. Conference Papers

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